microsoft fcfa applied research fund: economics, political ... · fcfa applied research fund:...
TRANSCRIPT
Microsoft
FCFAAppliedResearchFund:Economics,PoliticalEconomyandBehaviouralScienceofAccountingforLong-termClimateinDecisionMakingToday
ReviewPhase2015-03-10Note:Thisliteraturereviewwaspreparedtoinformtheaboveproject.Itispublishedhereindraftformtocontributetogreyliteratureonthistopic,andhasnotbeenpeerreviewed.
GCAP,VividEconomics,UKMetOfficeandAtkins
FCFAAppliedResearchFund:Economics,PoliticalEconomyandBehaviouralScienceofAccountingforLong-termClimateinDecisionMakingToday
ThisreportsummarisesthefindingsofPhase1oftheproject‘Economics,PoliticalEconomyandBehaviouralScienceofAccountingforLong-termClimateinDecisionMakingToday’.ThestudyisbeingundertakenbytheGlobalClimateAdaptationPartnership(GCAP),workingwithVividEconomics,theUKMetOfficeandAtkins.
SUMMARY
ThisreportsummarisesthefindingsofPhase1oftheproject‘Economics,PoliticalEconomyandBehaviouralScienceofAccountingforLong-termClimateinDecisionMakingToday’.ThestudyisbeingundertakenbytheGlobalClimateAdaptationPartnership(GCAP),workingwithVividEconomics,theUKMetOfficeandAtkins.ThisprojectisoneofanumberofresearchactivitiesthathavebeencommissionedbytheFutureClimateForAfrica(FCFA)programme,whichisadvancingscientificunderstandingofsub-SaharanAfricanclimateondecadaltimescalesandpromotingtheuseanduptakeofclimateinformationinlong-termclimate-resilientdevelopmentstrategies.Theaimsofthecurrentprojectaretoanalyseandidentifythetypesofdevelopmentdecisionsthatshouldbeactivelyaccountingforfuture(10years+)climateindecisionstakentoday,andtoadvancequantitativeevidenceonthistohelpinformdecisionsmadebydevelopmentpractitionersinAfrica.Theaimsofthefirstphaseoftheproject–summarisedinthisreport–aretoundertakeaninitialliteraturereviewonlong-livedpolicies,toidentifypracticalexamplesoflong-termdecisions,andtoreviewthebarrierstolong-termdecision-making.Thefindingsofthesetaskswillbeusedtoprovideinitialconclusionsanddevelopaframeworkandmethodologyforphase2,whichwillundertakeaseriesofeconomiccasestudies.Thefindingsofthereportaresummarisedbelow.TASK1:IDENTIFICATIONOFLONG-LIVEDPOLICIESANDINVESTMENTSThistaskhasexploredanumberofevidencelinestoidentifywhereandhowlong-livedpolices,plansandinvestmentsarebeingmadeacrosssub-SaharanAfricaandwherethesewillshapevulnerability.PolicyreviewThestudyhasfirstreviewedthepotentialareasofinterestforthestudy.ThisbuildsonearlierworkofHallegatteandRanger,whichindicatesapotentialfocusforinfrastructure(water,
irrigationandfloodprotectioninfrastructure,butalsoenergyandtransportinfrastructure)andplanning(especiallyurbanandcoastalplanning),inthe5to40yearperiodofinterestforthestudy.However,additionalreviewhighlightsthateveninthesecases,thepictureislikelytobemorenuanced,forexamplewhilemajorhydropowerschemesmightjustifyclimateriskscreening,smallerhydropowerplantsmaynot,andthejustificationforinvestmentinroadschemesmightbelimitedtositingandcriticalnodes(bridges).Thereviewhasalsoidentifiedsomeadditionalareasthatarerelevantforthistimeperiod.Thisincludesforestry,agriculturalland-useandcropplanning(especiallykeyexportcrops)andnaturalandsemi-naturalecosystemmanagement.DevelopmentplanningreviewInadditiontothereviewabove,thestudyhasalsoidentifiedthetypesofprocessesthatareinvolvedinmedium-long-termadaptation,asthesearecriticalinlookingatpracticalimplementation.Intheadaptationcontext–inSub-SaharanAfrica–thisiscentredonadaptationmainstreaming,i.e.theintegrationofadaptationintoexistingdevelopmentplanningprocesses(andsectors)andtheinclusioninprogrammeandprojectsafeguardandscreeningprocesses.Thefocusonmainstreaming,however,createsasetofadditionalproblems,associatedwiththetransferofpotentialcomplexmediumtolong-termadaptationdecisionstosectorsandactors.Anumberofrecentreviewshaveinvestigatedtheseissues,andhighlightedsomepracticalrecommendations,whicharesummarised.EconomicscopingInmanycases,themostimportantimpactsofclimatechangearelikelytoariseinthefuture.Thebenefitsofadaptingtothesechangesaccumulateoverlong,futuretimehorizons,whilethecostsareincurrednow.Usingthediscountratesconventionallyusedindevelopingcountries,futureadaptationbenefitsinthemediumtermandbeyondareextremelysmallincurrentterms.UsingahighlyillustrativeexampleandconventionaldiscountratesforLDCs(e.g.12%),thefuturestreamofadaptationbenefits(afewdecadesaway)needtobemanytimesgreaterthanupfrontadaptationcosts,topassaneconomiccost-benefitanalysis.Analysisoftheadaptationeconomicsliteratureshowsthislevelofbenefitswillberare,especiallygivenfuturebenefitsmaynotberealisedduetouncertainty.Inpracticalterms,thismeansthatthelimitedresourcesavailableinsuchcountrieswillmostbebetteroffspentelsewhere(i.e.togivemoreimmediatesocialbenefits)anditgivesmuchgreaterpreferencetono-regretadaptationoptionsastheseproduceimmediateeconomicbenefits.However,therearesomecaseswheremediumtolong-terminvestmentscouldbejustified,andthestudyhasexaminedthesewithsomesimpleexamples/schematics.Theyinclude:• Wherethecostsoflowcostoverdesign(orflexibilityorrobustness)areextremelylow;• Wherethecostsofclimatechangeandthebenefitsofadaptationareextremelyhigh(when
therearemajorshocksorindirecteffects,suchasfromfailureofcriticalinfrastructure);• Whenthereareearlybenefitsassociatedwithlonger-termadaptationoptions;• Whenthereisavalueofinformation(thoughthisismuchlowerthanintheOECDcontext);• Wheretherearefuturenon-marginaleffects.CapitalinvestmentsWhilesomecapitalinvestmentstodaymightappearvulnerabletofutureclimateortootherwiseaffectvulnerabilitytoclimatechange,theresultingcapitalstockmaydepreciatesofastthatitseconomiclifetimeisrelativelyshort.Thishasbeenreviewed,andfoundthatcapitaldepreciatesfasterindevelopingcountries.However,eventhoughdepreciationintheAfricancontextissignificantlyfasterthanintheUS,thissuggeststhatdecisionsonassetstakenoverthe
nextfewyearswilldeterminethecharacterofcapitalstockforthenextcoupleofdecades,atleast.QuantitativeassessmentofdecisionsthatlockinclimatevulnerabilityThestudyhasanalysedthepotentialinfrastructureinvestmentinfutureyearsinAfrica.Lookingacrosstheindicatorsofinfrastructureintensityasawhole,NigeriaappearstohavethehighestabsoluteinvestmentneedsinSub-SaharanAfrica–indeed,ithasthehighestneedsfornineofthetwelveindicatorsexaminedbyasignificantmargin.EthiopiaandtheDRCalsoscorehighlyonawiderangeofindicators.Inallthreecases,thekeydriverofthisisthelargesizeofthecountrybothintermsofpopulationandlandarea.Sucheffectsbecomemorepronouncedwhenconsideringforecastsofthesevariablessuchascitypopulationgrowth.However,thesesamecountriestypicallyperformpoorlywhenlookingattheenablingenvironmentforinfrastructureinvestment.CompositecreditratingsareroughlyaroundthemidpointofSub-SaharanAfricaindicatingeachcountryhaspooraccesstofinancefrominternationalsourceswhilethelevelofdomesticcreditavailableiswithinthelowestquartilesuggestingresourcesavailabledomesticallyareevenscarcer.ThesecountriesalsohaveanaverageWGIscorebetween20and30percentwhichmaymeanthatevenwithfavourableinvestmentconditions,publicinstitutionsmayfailtoorganiseandimplementsuchinvestments.Overall,itseemsthatNigeria,EthiopiaandtheDRCarelikelytoexperiencesomeinvestmentinlong-livedinfrastructureinthemediumterm,particularlyconcerningurbanplanning,housingandamenitieshowever,thereareunlikelytobetheleadersofSub-SaharanAfricathatthemainanalysissuggests.Twoparticularintensityindicatorsthatprovidedadifferentperspectiveweretheshareofirrigablelandequippedforirrigationandhydropowerproductionrelativetopotential.Withinboth,onlyasmallsubsetofcountriesislikelytoexperienceanysignificantinvestmentinthefuture.WhiletheDRCstillhasthehighestinvestmentneedsforirrigationandEthiopiaforhydropower,othercountriessuchasAngola,MozambiqueandZambiaalsorequiredasubstantialamount.Thesethreecountriesscoredmoderatelyonboththeinvestmentclimateindicatorsandthequalityofgovernanceindicatorsuggestingthatamoderatelevelofinvestmentininfrastructureinthesesectorsislikely.SouthAfricahadrelativelyhighinvestmentneedsforbotheducationalandsocialprotectioninfrastructure.SimilartotheeffectsofNigeria’slargepopulation,thiswascausedprimarilybySouthAfrica’srelativelyhighGDPwhichcausedevenamodestintensitygaptotranslatetosubstantialabsoluteinvestmentneeds.SouthAfricaalsoscoredrelativelyhighlyinboththeaccesstofinanceindicatorsandtheaverageWGIscoresuggestingthatiftherewassufficientdemand,theopportunityforinvestmentsisavailable.Overall,thisindicatesthatsignificantinvestmentislikelytooccurininfrastructuretoprovidebotheducationandsocialandlabourprotectioninthefuture.TASK2:PRACTICALEXAMPLESOFLONG-TERMDECISIONSThistaskhasexploredanumberofevidencelines.
First,thestudyhasreviewedtheevidencebaseonthecostsandbenefitsofadaptationinAfrica.Thishasexpandedconsiderablyinrecentyears,duetoalargenumberofglobalandcountrylevelinitiativesontheeconomicsofadaptation,andalsosectoralstudiesthatapplyexistingoptionstonewcontextsorlocations.However,themajorityoftheseusescenario-basedimpactassessment,andarethusoflimitedpracticalforrealmediumtolong-termadaptationdecisionmaking.Second,thestudyhasbrieflyreviewedthemethodsandapplicationofnewdecisionsupporttoolsforadaptation,manyofwhicharetargetedtoaddressinguncertaintyinmediumtolong-termdecisions.Therearenowanumberofstudiesusingiterativeriskmanagement,realoptionsanalysisandrobustdecisionmaking,thoughthereareonlyahandfulofsuchstudiesinAfrica.However,thesenewmethodsfordecision-makingareresource-intensiveandcomplextouse.Whilsttheyhavepotentialapplicationformajordevelopmentinitiativesandinvestments,theyhavelimitedapplicationformoreroutineapplication(orinmainstreaming)inAfrica:thepriorityisthereforetodeveloppragmatic,light-touch,approachesthatcapturethecoreconceptsofthesenewmethodsandmaintainadegreeofeconomicrigour.TASK3BARRIERSTOLONG-TERMDECISIONSBarriersorconstraintstoadaptationarefactorsthatmakeithardertoplanandimplementadaptationactions.Barrierswillmakeadaptationlessefficientorlesseffective.Alternatively,itmayrequirechangesthatleadtomissedopportunitiesorhighercosts.Thestudyhasreviewedtheliteratureonbarrierstoadaptation.Ithasalsoundertakenafurthermoredetailedreviewinrelationtobehavioraleconomics.Finally,itishasdrawnupaninitialtableofhowthebarriersmightaffectthemediumtolong-termadaptationdecisionsidentifiedinprevioussections.ReviewoftheliteratureThemainbarrierstosociallyefficientadaptationaremarketfailures,policyfailures,governancefailuresandbehavioralbarriers.Marketfailurescanoccure.g.duetolackofinformation,thepresenceofexternalitiesandpublicgoods,informationasymmetryandmisalignedincentives.Economictheoryappliedtoadaptation,aswellasempiricalobservations,indicatethatsuchactionswillnotreceiveappropriatelevelsofprivateinvestment.Forexample,underdifferentmarketstructures(monopoly,oligopolyorperfectcompetition),theabilityofinvestorstoreapthebenefitsofadaptationwillvary,andthereforealsotheirincentivestoinvestinit.Policyfailuresoccurwhenconflictingpolicyobjectivesco-exist(whichisoften)andtherearenotappropriatemechanismsforaddressingthesetrade-offs,andwhenthecurrentstructureofinstitutionsandregulatorypoliciesispoorlyalignedtoaccountforadaptationobjectives.Forexample,urbandevelopmentobjectivesmaynottakeintoaccountthevulnerabilityofassetsandhumansystemstoclimaticstresses.Also,whenpoliciesresultinmarketdistortions(e.g.priceorincomesubsidies),peoplewillunder-orover-adaptdependingonhowtheiradaptationchoiceswilltranslateintoincomechanges.Governancefailuresrefertoineffectiveinstitutionaldecision-makingprocesses.Adaptationtypicallyrequiresmultipleactorsandinstitutionswithdifferentobjectives,jurisdictional
authorityandlevelsofpowerandresources.Thecomplexitiesofgovernancenetworkscanindeedconstrainadaptation.Overlappingmandatesofgovernmententitiestendtocreateconflictsandslowadaptiveresponses.Further,lengthybureaucraticprocessesandlackoftransparencyareanimpedimenttofiscalplanningandaccesstofinance,particularlyrelevantfordevelopingcountries.Poor-orlackof-leadership,lackofaclearmandate,andtheshort-termpoliticalcyclecanalsorepresentbarrierstoeffectivedecision-making.Corruptionwithininstitutionsalsounderminesadaptationefforts.Behaviouralbarriersareconcernedwiththeobservedinabilityofindividualstotakewhatappeartoberationaldecisions(i.e.tomaximizetheirnetbenefitsorutilities)andwiththeircognitivelimitationinattemptingtoachievetheirgoals.Thislimitationmanifestsitselfasinertia,procrastination,andtheuseoftime-inconsistentdiscounting.Socialvaluesandbeliefscanalsosupportorhamperadaptation,insofarastheyframehowsocietiesdeveloprulesandinstitutionstogovernrisk,andtomanagesocialchangeandtheallocationofscarceresources.Further,individuals,institutionsandthenaturalenvironmentwillclearlyadaptwithintheboundariesoftheiradaptivecapacity,andphysicalandbiologicalconstraints.Gender,age,education,accesstoinfrastructureandfinance,andaccesstomarketsandtechnologyareallelementsthatdeterminetheadaptivecapacityofsocialsystems.Naturalsystems’abilitytoadaptwillbepossiblewithincertainclimaticthresholds,andcanbehamperedbyothernon-climaticstresses,andthepresenceofphysicalbarriers(e.g.thelackofcorridorsforspeciesmigration).MappingofbarrierstodecisionsThesectionsabovehighlightthepotentialbarrierstoadaptation.However,thisprovidesatheoreticalperspective.Akeyissueforthecurrentstudyistotranslatethisintoamorepracticalsetting,andthenlookatpotentialsolutions.Toadvancethisanalysis,thestudyhasmappedthepotentialbarriersidentifiedabovetothepriorityareaswehaveidentifiedformediumtolong-termadaptationdecisions–focusingonspatialplanning,serviceandinfrastructuredelivery-andproposessomepossiblesolutions.
TABLE OF CONTENTS
INTRODUCTION.............................................................................................................................................1
TASK1:IDENTIFICATIONOFLONG-LIVEDPOLICIESANDINVESTMENTS.........................................................2
LITERATUREREVIEW................................................................................................................................................2REVIEWOFDEVELOPMENTPLANNING(PUBLICPOLICY)................................................................................................11THEECONOMICCASEFORACTION(ORNOT).............................................................................................................15DISCUSSION.........................................................................................................................................................23CAPITALINVESTMENTS...........................................................................................................................................24QUANTITATIVEASSESSMENTOFDECISIONSTHATLOCKINCLIMATEVULNERABILITY.............................................................27
TASK2:PRACTICALEXAMPLESOFLONG-TERMDECISIONS..........................................................................47
STUDIESONTHEECONOMICSOFADAPTATIONINAFRICA..............................................................................................47STUDIESONLONG-TERMADAPTATIONDECISIONMAKING............................................................................................50DISCUSSION.........................................................................................................................................................57
TASK3:BARRIERSTOLONG-TERMDECISIONS.............................................................................................58
LITERATUREREVIEWONTHEBARRIERSTOADAPTATION................................................................................................58MAPPINGOFBARRIERSTODECISIONS.......................................................................................................................72
REFERENCES.................................................................................................................................................82
1
INTRODUCTION TheUK'sDepartmentforInternationalDevelopment(DFID)andtheNaturalEnvironmentResearchCouncil(NERC)arejointlyfundingafive-yearinternationalresearchprogrammecalledFutureClimateForAfrica(FCFA).Theprogrammeaimstoadvancescientificunderstandingofsub-SaharanAfricanclimateondecadaltimescalesandpromotebettercommunication,useanduptakeofclimateinformationintolong-termclimate-resilientdevelopmentstrategies.TohelpinformtheFCFAprogramme,anumberofresearchprojectshavebeencommissioned,includingthisprojecton‘TheEconomics,PoliticalEconomyandBehaviouralScienceofAccountingforLong-termClimateinDecisionMakingToday’.ThestudyisbeingundertakenbytheGlobalClimateAdaptationPartnership(GCAP),workingwithVividEconomics,theUKMetOfficeandAtkins.Theprojectaimstoanalyseandidentifythetypesofdevelopmentdecisionsthatshouldbeactivelyaccountingforfuture(10years+)climateindecisionstakentoday,andwillreviewthepoliticaleconomyandotherbarrierstoachievingthis.ThemainobjectiveistoprovidequantitativeevidenceonadaptationstrategiesthatwillhelptoinformdecisionsmadebydevelopmentpractitionersinAfrica.ThefindingsoftheprojectwillfeedintotheFCFAresearchconsortiaandCCKEUnittohelpinformtheirappliedresearchanddecisionsupportservicestovariousstakeholders.Specificallytheprojectaimsto:
• Developandapplyasimpleframeworkthatidentifieswhererealpolicies,programmesandinvestmentsarebeingmadetodaythathavelong-termimplicationsforthevulnerabilityoflocalpeopleoreconomiesinAfricaandwhereitwouldberationaltoaccountforfutureclimateindecisionmakingtoday.
• IdentifyexamplesinAfricaofwheresuchlong-termpolicies,programmesandinvestmentsarebeingmadethathaveorhavenotsuccessfullyconsideredfutureclimateintheirimplementation.
• Reviewtheliteratureonthepotentialbarrierstosucharationalapproachinpractice,withparticularfocusonthepoliticaleconomyandbehaviouralbarriers.
• Forasmallsetofrelevant(illustrative)cases,providequantitativeevidenceontheeconomicrationaleforadapting(ornot)suchdecisionstocopewithfuture(i.e.10years+)climateandwhererelevant,strategiesforimplementingadaptation,includingtheappropriatetimingandsequencingofmeasures.
Theprojectisbrokenintotwophases.Phase1includesthefollowingtasks:
a) Initialliteraturereviewonlong-livedpolicies;
b) Identificationofpracticalexamplesoflong-termdecisions;
c) Literaturereviewonthebarrierstolong-termdecision-making;
d) Developmentofinitialconclusionsanddevelopmentofaframeworkandmethodologyforphase2,whichwillundertakenewcasestudyanalysisoftheeconomicsoflong-termpolicies,plansorinvestments,toexplorewhereitwouldberationaltoaccountforfutureclimateindecisionmakingtoday
Thereportsetsoutthereviewfindingsforeachofthesefourtasksinturn.
2
TASK 1: IDENTIFICATION OF LONG-LIVED POLICIES AND INVESTMENTS
Theaimofthistaskistoreviewtheacademicandgreyliteratureassessingwhereandhowlong-livedpolices,plansandinvestmentsarebeingmadeacrosssub-SaharanAfricaandwherethesewillshapevulnerability,withfocusoneconomicandsimilarlyquantitativeliterature.Toadvancethisanumberofevidencelineshavebeeninvestigated.Theseare:
• Toreviewtheliteraturetoidentifylong-livedpolicies,plansandinvestmentsthatarepotentiallyvulnerabletomediumtolong-termclimatechange.
• Toreviewthoseareasofdevelopment(fromanationaltolocalpublicdevelopmentplanningperspective)toidentifyareasofrelevanceandentrypoints.
• Toinvestigatetheeconomiccaseformediumtolong-termclimateinterventions.
• ToassessfuturecapitalinvestmentsandprioritiesforadaptationinAfrica.
Literature Review Thistaskhasreviewedtheliteraturetoidentifypotentiallivedpolicies,plansandinvestments.FuturePriorityAreasThereisaliteraturethatexaminestypesofinvestmentsthatmightbeatriskfromfutureclimatechange,basedonlifetimes.Hallegatte(2009)identifiedalistofsectorsinwhichclimatechangeshouldalreadybetakenintoaccount,becauseoftheirinvestmenttimescalesandtheirexposuretoclimateconditions,shownbelow.Sector Timescale(year) Exposure
Waterinfrastructures(e.g.,dams,reservoirs) 30–200 +++Land-useplanning(e.g.,infloodplainorcoastalareas) >100 +++Coastlineandflooddefences(e.g.,dikes,seawalls) >50 +++Buildingandhousing(e.g.,insulation,windows) 30–150 ++Transportationinfrastructure(e.g.,port,bridges) 30–200 +Urbanism(e.g.,urbandensity,parks) >100 +Energyproduction(e.g.,nuclearplantcoolingsystem) 20–70 +Source:Hallegate(2009).Stafford-Smithetal.2011presentasimilarconceptgraphically.
3
Rangeretal.(2014),updatingStafford-Smithetal.2011,outlinedthetimescalesofdifferenttypesofclimate-sensitivedecisions,asbelow.Applyingtoaworldbankportfoliofor250projects,theyreportthatbetween2%and30%ofthesemayrequireactionnowto“future-proof”investmentsandpolicies.
Source:Rangeretal.(2014),updatingStafford-Smithetal.2011Thesestudiesbothindicateapotentialfocusoninfrastructure(notablywater,irrigationandfloodprotectioninfrastructure,butalsoenergyandtransportinfrastructure)andplanning(especiallyurbanandcoastalplanning),inthe5to40yearperiodofinterestforthestudy.Additionalareasofthebuiltenvironment(Hallegatte)andnaturalresourcemanagement(Ranger)arealsoincluded.Whilesocialprotectionisassignedadecadaltime-frame,thetermsofreferencehighlightthisisapotentialareaofinterest,sothisisalsoincluded.ThisfindingwasgenerallyborneoutintheFCFApilotstudies(notablyinRwanda,butalsoinMaputo),whichidentifiedinfrastructureandplanningaskeypriorityareas.However,theRwandapilot(Watkissetal.,2014)alsohighlightedamorenuancedpicture.Asexamples:
• Whilelargehydropowerinvestmentwasconsideredapriorityforclimateriskscreening,thepaybackperiodsforsmallhydrodidnotjustifyactionforinvestors.ThiswasbecausecompanieswereborrowingfromBankofRwandaatinterestratesof18%,orfromtheFONERWAclimatefundat11%,andthustherewasnofinancialincentivetoincreaseup
4
frontdesigncostsforfuturerisks(notingthismightnotbeoptimalfromasocietalpointofview,especiallywhenschemesaredesignedtotransfertogovernmentinthelonger-term.
• Fortheroadsector,therewasacaseofmal-adaptationidentifiedforanactualpolicy.Thisinvolvedacommitmenttoclimate-proofruralfeederroadsintheagriculturaldevelopmentstrategy.Thisinvolvesacostpenalty,whichreducesthebudgetavailable,i.e.itleadstobuildingasmallernumberofhigherqualityroads,thanworkingwithcurrentdesignstandards.Thekeyissuehereisthatthepavementlifetimeofroadsisaroundadecade,i.e.theywillnotbeexposedtolong-termclimatechange,thusthisinvestmentisapotentialwasteofresource.Thestudynotedthatsitingroadstoavoidcurrenthighriskareasissensible,toavoidlock-intoclimaterisks(e.g.floods),anditwillbecost-effectivetoensuresomedegreeofcurrentresilience,allowsomeflexibilityforlaterupgrades,ortofocusoncriticalnodeswithlonglife-times(bridges).
• Inthewatersector,thelong-termintegratedwaterresourcesplan,whichextendsoutto2040,hadnotconsideredclimatechange.Thisisapotentialomission,especiallygivenfutureirrigationplans.However,theroleofclimatechange(andthelevelofuncertainty)ininfluencingfuturewaterdemandwassmallcomparedtosocio-economicdevelopment,i.e.climateisunlikelytobethemaindriverforthesector.Furthermore,asmostclimateprojectionsindicatedasmallincreaseinwateravailability,theperceptionofclimateriskwaslow(thoughtheCMIP5projectionsindicateadifferentoutcome,whichmeansthisassumptionwasmisleading).
Atthesametime,theFCFApilotsidentifiedsomeareasnotcoveredintheHallegateandRangerstudies,including:
• Forestrymanagement(commercialandmanagementofnaturalandsemi-naturalareas).Commercialforestryusesalong-termfinancialmodel.Thismeansithassimilarattributestoinfrastructure,inthattherearerisksoffutureclimatechange,buttheseareevenmorepronouncedbecausereturnsoninvestmentariseinthelonger-termwhentreesareharvested.Forestsarealsoclimatesensitive(Ravindranath,2007:Dasguptaetal,2014:Setteleetal.,2014),andmaybeaffectedbychangingtrendsoverfuturedecades(e.g.fromchangesingrowthorquality,fromincidenceofpestanddisease,orfromdamageassociatedwithvariabilityincludingwind).Thisleadstodualfactorsinrelationtotheplantingofvarieties(today)thatwillbesuitableforthefuturebio-climaticzoneunderclimatechange(ormoreaccuratelyachangingclimateovertime)aswellasmeasuresthatreducerisksassociatedwithvariability.TheseissuesalsoapplytoREDD+initiatives.Similarissuesariseforconservationandmanagementofnaturalandsemi-naturalforests,wheretheremaybeaneedforearlyplanningofbufferzones(landmanagement)oractiveconservationoptions(e.g.translocation).
• Exportcropdevelopment.AgricultureisusuallyanimportantcontributortoexportvalueinAfricancountries,oftenassociatedwithclimatesensitivecropssuchascoffeeandtea(e.g.inEthiopia,coffeeisaround75%ofexportcommodityvalueanditisamajorpartofthefuturegrowthplansofthecountry).Thesecropshavelongerlife-cyclesthancerealcrops(takingfivetotenyearsforplantationstoestablishandbecomeproductive),andtheyalsohavelongplanningcycles(e.g.thetimetoswitchcoffeevarieties,fromearlyR&D,testing,roll-out,maturationandharvestingisover20years).Studiesindicatethatfuturebio-climaticshiftscouldmakeareasunsuitableforcoffee(Daviesetal.,2012)andthusearlyadaptationisimportant(asidentifiedintheEthiopianClimateResilientStrategy,Watkissetal.,2013).Inmanycountries,suchasRwanda,thereareplanstoincreasetheareasofland
5
undercultivationforteaorcoffee,whichalsoinvolvesearlyland-useplanningdecisionsthatwilllock-inruraldevelopmentpatterns.Theremayalsobesimilarissuesforothercrops,e.g.chocolateinWestAfrica,orvinicultureinSouthAfrica.
• Ecosystemservicesandlimits.Naturalandsemi-naturalecosystems–andtheservicestheyprovide–tendtobehighlyclimatesensitiveandhavelowadaptivecapacity.Climatechangewillshiftgeographicranges,seasonalactivities,migrationpatterns,abundances,andspeciesinteractions,andhasthepotentialtoincreasetherateofspeciesextinctioninthesecondhalfofthe21stcentury(Setteleetal.,2014).Theseincludemajoreffectsthatcouldaffecttheprovisionofecosystemservices,whichcurrentlyunderpinmanyeconomiesinAfrica.Whiletherearelowregretoptionsbuiltaroundexistingconservationandprotection,thisisalsoanareawheremoresubstantialadaptationmaybeneeded.Thereisthepotentialforearlyactionfromaprecautionaryperspectivewherethereareverylargerisks(eitherhighannuallevel,exceedanceofthresholds,orlarge-scaleorirreversiblemajoreffects)and/orwherealackofshort-termactioncouldlockinthisfuture(systemic)damagetothesesystems.Asaminimum,earlymonitoringandR&Disessential.
FrameworksWhiletheinformationaboveprovidessomegeneralinformationonpotentialareasoffocus,itisalsonecessarytolookatthejustificationforearlydecisionmakingformediumtolong-termdecisionmaking,andtoidentifytypesofadaptationdecisions.Earlierstudiesconsideredthepotentialforlonger-termdecisionmakingbyusingtypologiesofadaptation,oftenpresentingtheseasbuildingblocksoraspectrumofoptions(McGrayetal.,2007;KleinandPersson,2008).Theseincludeddifferentiatedactivitiesincludingaddressingcurrentvulnerability,buildingadaptivecapacity,mainstreamingclimaterisks,andpreparingforandtacklinglonger-termchallenges–thelattertwobeingofparticularrelevanceforthisstudy.However,withthegreaterrecognitionoftheuncertaintychallengesofadaptation(e.g.UNFCCC,2009;Hallegatte,2009;WilbyandDessai,2010:WorldBank,2012),therehasbeenashiftintheliterature,awayfrompolicy-firstimpactassessmenttoiterativeclimateriskmanagement,asseeninrecentIPCCCreviewsintheSREXand5thAssessmentReport(IPCC,2012:IPCC,2014).Asaresult,morerecentupdatesoftypologiesofadaptationhavemadethemmoredecision-led.Theyhavealsoalignedthetypesofactivitiesanddecisionstoiterativedecisionmakingframeworks(e.g.Rangeretal.,2010;WatkissandHunt,2011;DFID,2014).Importantlythisrecognisesthateachactivity(orbuildingblock)isadifferentproblemtype,requiringdifferentinformation,andvaryingmethodsofeconomicappraisal(Li,MullanandHelgeson,2015).AnexampleofsuchatypologyisincludedinBox1.Theevolutionofclimatechangeispresentedatthetopofthefigure,asaprocessthatstartswithcurrentclimatevariabilityandevolvesovertimewithincreasinguncertainty.Inresponse,thebottomofthefigureoutlinesthreedifferenttypesofadaptationresponse,whichaddresseconomicanduncertaintychallenges.Allthreetypesneedtobeconsideredtogetherinanintegratedadaptationstrategy,andtheuseofanadaptationpathwayapproachcancaptureandlinkthedifferentactivitiestogetherovertime(Watkiss,2012:Downing,2012).Forthisstudy,thepriorityareaofinterestisfortype2and3adaptation,i.e.wherethereisastrongerfutureclimatecomponent.
6
Box1:IterativeAdaptiveManagement.
Thefigurebelowhighlightsthepotentialtypesofmediumtolong-termadaptationdecisions,setwithinaframeworkofiterativeclimateriskmanagement.
Source:Watkissetal,2014(DFID,2014),updatedfromWatkissandHunt,2011.First,itprioritisesearlyactionstoaddressthecurrentadaptationdeficitandhelptobuildresilienceforthefuture.Thisinvolvesearlycapacity-buildingandtheintroductionoflow-andno-regretactions,whichleadtoimmediateeconomicbenefits.Suchactionsaregroundedincurrentpolicyandcanoftenuseexistingdecisionsupporttools.However,theyareoflessrelevanceforthisstudy.Second,thereisearlyactiontointegrateadaptationintocurrentdecisionsoractivitieswithlonglife-times,suchasinfrastructureorplanning.Thisrequiresalternativeinformationsourcesandmethodstoabove,becauseoftheneedtoconsiderfutureclimatechangeuncertainty.Italsorecognisesthatthereisaneedtoconsideroptionsinadifferentwaytonormalappraisal,suchasconsideringlow-costoptions,flexibilityorrobustnesstoaddressfutureuncertainty.Finally,thereisaneedtoconsiderthepotentialmajorimpactsofclimatechange,notingthepossiblelongtime-scalesandhighuncertainty.Theconsiderationoftheselonger-termissuesinvolvesimportantchallengesandusuallyrequiresnewapproachesorthinkingbuiltaroundadaptivemanagement.Thisentailslearningfromearlyactivities,theidentificationofiterativeportfoliosthatcanbebroughtforwardordelayedaccordingtohowthefuturedevelops,andearlyactionstoaddressirreversibility,lock-inandencouragetransformation.
7
Othersimilarframeworksexist.Fankhauseretal.(2013)outlinesareasforearlyadaptationas:• Adaptationswithearly,robustbenefits.Fast-trackingadaptationmakessenseifthe
proposedmeasureshaveimmediate,robustbenefitsthatwouldotherwisebeforgone,forexample,wherethereisanexistingvulnerabilityorthereareexpectednear-termimpactsfromclimatechange.
• ‘Low-regrets’adaptationmeasureswithlongleadtimes.Itmakessensetofast-track‘low-regrets’adaptationsthathavelongleadtimes,suchasresearchanddevelopment,evenifthebenefitswillnotaccrueuntillater.
• Areaswheredecisionstodaycould‘lock-in’vulnerabilityprofilesforalongtime.Fast-trackingadaptationisdesirableifawrongdecisiontodaymakesusmorevulnerableinthefutureandifthoseeffectsarecostlytoreverse.Severalstrategicdecisionspotentiallyfallintothiscategory,includingthoseonlong-terminfrastructure(e.g.thelocationofnewairports,raillinksandwindfarms),land-useplanningandthemanagementofdevelopmenttrends,suchasregionalwaterdemand.Thisincludes:
o Landmanagementandlong-livedinvestmentandlocationdecisionsconcerningbuildingsandinfrastructurewillhavelong-lastingeffectsonsocietalvulnerabilitytoclimate.Thesedecisionscanbedifficultandcostlytoreverseorretrofitlater.
o Afailuretomanageotherdriversofstresses,suchasgrowingdemandforwater,risingandunstablefoodprices,environmentaldegradationandincreasingprevalenceofdisease,couldalsolock-infuturevulnerabilitytoclimatechange.Tacklingtheseissuesnowcanstrengthenlong-termresilienceandadaptivecapacity
Illustrativedecision-makingprocessforprioritisingadaptation
Source:Fankhauseretal.,2010.Italsohighlights:• Includingsafetymarginsformeasuresandpoliciestodaytocopewithawiderrangeof
possibleclimateconditions.• Designingmeasuresandpoliciestodaythatcanbeeasilyandinexpensivelyadjustedlaterto
copewithfutureclimateconditions.
8
• Designingstrategiesthatuseapackageofadaptationmeasuresthataresequencedovertimetoreducecurrentclimaterisk,whilemaintainingflexibilitytocopewithfuturerisks.
• Reducingthelifetimeofdecisions.TheDFIDTopicGuidance(Ranger,2013)takesthisfurtherandexaminestheseconceptsinthedevelopmentcontext,identifyinggenericareasfordevelopment,shownbelow.
Genericclassesofpriorityadaptationmeasures(Fankhauseretal.2013),withspecific
applicationstodevelopmentinterventions(basedonOECD2009andRangerandGarbett-
Shiels,2012).
GenericAreaofPriorityAction
Source:Fankhauseretal.2013Applicationtoprioritiesfordevelopmentinterventions
Sources:OECD(2009)andRangerandGarbett-Shiels,2012• Adaptationswithearly,robust
benefits.Fast-trackingadaptationmakessenseiftheproposedmeasureshaveimmediate,robustbenefitsthatwouldbeotherwisebeforgone;forexample,wherethereisanexistingvulnerabilityorexpectednear-termimpactsfromclimatechange[low-regrets,seeSectionIII.1]
• Investinclimate-resilientdevelopment.Well-designeddevelopmentpoliciescanbeano-regretformofadaptationthroughreducingsocialandeconomicvulnerability.
• Reducevulnerabilitytocurrentclimatevariabilityandextremeweatherevents.Disasterriskmanagementcanbealow-regretadaptation,bringingimmediatebenefits.
• Improvetheavailabilityandqualityofclimateinformation.Includingmonitoringsystems,futurescenariosandvulnerabilityassessments.
• Adoptmeasurestoreducetheimmediateimpactsofclimatechangeandotherstressesonthemostvulnerablepeopleandsystems.Somehumanandnaturalsystems,includingterrestrial,marineandfreshwaterecosystems,canbevulnerabletoevensmallchangesinclimate.Actionscouldincludeenhancingtheimplementationofrelevantmultilateralandregionalenvironmentalagreement.
• Reviewandadjustregulationsandstandardstoreflectclimatechangeimpacts.Forexample,tohelptoremoveanybarrierstoadaptationorperverseincentives(overcomemarketfailures)onfirmsorindividuals(BoxX)
•Areaswheredecisionstodaycould‘lock-in’vulnerabilityprofilesforalongtime.Fast-trackingadaptationisdesirableiftoday’sdecisionscouldcommitsocietytoaparticularmorevulnerabledevelopmentpaththat
• Incorporateclimatechangeandadaptationconsiderationswithinnationaldevelopmentpolicies,includinglong-termvisions,povertyreduction,economicgrowthandsustainabledevelopmentstrategies.Avoidmakingdecisionstodayinwaysthatcouldlock-inimpactsorincreasefuturevulnerability,insteadseeklow-costwaystodesignstrategies
9
wouldbecostlytoreverselater.Severalstrategicdecisionsfallintothiscategory,includinglong-terminfrastructure,land-useplanningandmanagingdevelopmenttrendssuchasgrowingwaterdemand.
sothattheyenhancelong-termresilience.• Wheredealingwithexpensive,long-termprojects,suchas
publicinfrastructureorurbanplanning,seekoptionsandstrategiesthatwillbuildinflexibilitytocopewiththeuncertaintyoverfutureclimate.Thisisrelevanttonewprojects,butalsoupgradesandmaintenancecycles.
• Buildingadaptivecapacity • Buildingthelong-termcapacityforclimate-resilientdevelopment,includingdevelopingappropriateinstitutionalstructures,skillsandknowledgeatmultiplelevels
• ‘Low-regret’adaptationmeasureswithlongleadtimes.Itmakessensetofast-tracklow-regretadaptationsthathavelongleadtimes,suchasresearchanddevelopment,evenifthebenefitswillnotbeaccrueduntillater.
• Supportingthedevelopmentanddeploymentofrelevantagriculturaltechnologiesandotherinnovationthatcanreducelong-termsocialandeconomicvulnerabilities.
Rangeretal.(2014)identifiedthreeareaswhereadditionalactiontodayisjustifiedtoadapttofuturerisks:1. Long-lived,investmentswithlargesunkcosts,suchashydropowerstations,roads,dams,
andotherinfrastructure.Afailuretoaccountforclimatechangeupfrontinsuchlong-livedinvestmentscouldmeanthattheyunderperform(e.g.,inthecaseofwatersupplysystemsandhydropower)orbecomeexposedtoincreasingdamage.Thiscouldmeanthatinvestmentsneedtoberetrofittedorreplacedprematurely,imposinggreatercosts.Forexample,thelifetimeofdifferentinvestments;newtransportandenergyinfrastructurecanlastfor40yearsormore,largedamsforatleast60years,andpatternsofurbandevelopment(thelayoutofsuburbs,roads,andotherinfrastructureinacity),formorethan100years.Theclimateislikelytobeverydifferentonthesetimescales.Capitalinvestmentsareparticularlypronetomaladaptationbecausetheytendtobedifficulttochange.
2. Long-termplanningandpolicy-making,suchasgrowthstrategies,sectordevelopmentplans,apovertyreductionstrategy,coastaldevelopmentplans,droughtcontingencyplans,andurbanzoningcanhavefar-reachingandcomplexconsequencesthatinfluencevulnerabilityfordecades.Insomecases,theywillhavepositiveco-benefitsforlong-termresilience,forexample,throughstrengtheninggovernance,buildingcapacity,andincreasingaccesstocredit.Butinafewcasesthereisariskofmaladaptationwhenpeopleareinadvertentlycommittedtogreateranddifficult-to-reversedecisionsthatmayincreasetheriskfromclimatechange.Thisincludes:
• SocialprotectionsystemscanincreaseresiliencetoclimateshocksbutwillneedtobeadjustedovertimetocopewiththechangingprofileofvulnerabilityandclimaterisksIfthisadaptabilityisnotbuiltinfromthestart,systemscanbedifficulttoadjustovertime,duetopolitical,social,orlegislativebarriers,makingthemlesseffective.
• Aprogrammethatpromotedwater-intensiveagriculturemaychangebehavioursemi-irreversiblyandbedetrimentaliftheclimatebecamedrier.
• Aruralroadsprogrammethatbuiltintersectionsonfloodplainscouldleadtourbandevelopmentandputthesecommunitiesatriskinthelongterm.
• Aprojectthatbuiltschoolsonafloodplaincould,atbest,limitaccesstoeducationforlocalchildren,oratworst,putthemindanger.
• Evenshort-livedprojects,likeclimate-smartagricultureorruraldevelopmentprogrammes,cancumulativelyadd-uptomajorchangesinlong-termresilienceinunexpectedways.
10
3. Interventionswithlonglead-times:incaseswheremeasureswilltakemanyyearstoimplement,itmayneedtostartnow.Forexample:
• Removingbarrierstoadaptationandbuildingadaptivecapacitycantaketime,asitcaninvolvemajorchangesininstitutional,governance,andlegislativestructures(e.g.,landandwaterrights),decisionprocesses,andculturalnormsandbehaviour.
• Researchanddevelopment,forexample,todevelopandpilotnewagriculturaltechnologiescanalsotakemanyyears.
• Changinglivelihoodsandmigration,forexample,enablingruralcommunitiesinunsustainableareastomoveandseekneweconomicopportunitiescantaketime.
Rangeretal.(2014)presentedadecisiontreetohelpdevelopmentpractitionersscreenwhereadevelopmentinterventionislikelytorequiresomeadaptationtodaytoaccountforfuture(10years+)climate.Thisisshownbelow.Thisleadstoasetofcriteriathatcanhelpinidentifyingprojectswhereitmaybebeneficialtofuture-proofnow.Ingeneral,wheretheprojectoritsoutcomesarelong-lived(i.e.,long-term),difficult-to-adjust,andhaveahighcostorimpact(i.e.,highstakes)thenclimatechangeislikelytobeacentralfactorindesigntoday.Thisframeworkisillustratedbythelowerthreeblocks.
Simpleframeworkillustratingtheconditionsunderwhichlong-termclimatechangeislikelyto
beanimportantfactorinthedesignofaprogramme
Source:Rangeretal.2014Afinalmatrix,fromDercon2014,identifieswhereinterventionsarelikelytobehighvalueformoneytoday(ingreen)andwhereinterventionswilllikelyrequiresomeadaptationtoreducetheriskoflock-in(inred).
11
Review of Development Planning (Public Policy) Thesectionaboveidentifiestypesoflivedpolicies,plansandinvestments,andawaytoviewpotentialearlyadaptationformediumtolong-termdecisions.However,itisalsousefultoidentifythetypesofprocessesthatareinvolvedwiththesedecisions,asthesearecriticalinlookingatpracticalimplementationofadaptation(IDRC,2015)1.Akeyissuehererelatestorelevantentrypoints(OECD,2009;UNDP-UNEP,2012),i.e.theopportunitiesinthenational,sectororprojectplanningprocesswhereclimateriskconsiderationscanbestbeintegrated.Theseareparticularlyimportantforadaptation,becausethereisacurrentfocusonmainstreaming,whichseekstointegrateadaptationintoexistingprocessesanddecision-makingacrossarangeofpolicyareas,ratherthanintroducingstand-aloneadaptationpolicy.Inthisregard,adaptationisverydifferenttomitigation(Watkiss,BenzieandKlein,2015)andthisisduetothestrongoverlapbetweenadaptationandexistingactivitiesthataddresscurrentclimateresilience(e.g.disasterriskreduction,watermanagement,etc.).Policymeasuresthatwillaffectadaptationareoftenimplementedfornon-climatereasons,withmultipleobjectivesandancillarycostsandbenefitsthatarematerialtotheoverallchoiceofthemeasures.Itisthereforeimportanttounderstandthecontextforaninterventionanddecision,includingtheexistingpolicyandobjectives,non-climaticdrivers,andthecurrentdecision-makingprocess.Asanexample,resiliencemaybemainstreamedaspartofanurbanregenerationprogramme,butthedesignofsuchaprogrammewillbedominatedbylocal1ThissectionsummarisesrecentworkundertakenbytheprojectteamaspartoftheIDRCfundedprojectontheEconomicsofClimateResilience,andwillbepublishedintheOECDbook‘ECONOMICSOFADAPTATIONINOECDCOUNTRIES’inJune2015.
12
economicdevelopmentobjectivesandotherdrivers,suchasdemographicandland-usechange.Suchamainstreamingpracticewillalsorequireagoodunderstandingoftheindividualorganisations,institutionalnetworksandprocessesmakingrelevantdecisions.Critically,allofthesewilldifferwitheachspecificadaptationproblem.IntheAfricancontext,thisthereforerequiresanunderstandingofthelinksbetweenclimatechangeadaptationandnationalorsectordevelopmentpriorities.Itisalsoimportanttoconsiderhowtheselinkagescascadefromhighlevelstrategicpolicythroughtoimplementation,aswellashowtheyaresituatedwithintheinstitutionalandpoliticalcontexts.Interesting,inadevelopingcountrycontext,mainstreamingactivitiesusuallyfollowaslightlydifferentpaththanindevelopedcountries,withdifferententrypoints,reflectingthedifferencesinnationalstrategicplanning.Inthiscontext,thereareasetofentrypointsformainstreaming,outlinedinthetablebelow(UNDP-UNEP,2011)notingthattheseoftenoperatethroughdifferentorganisationalleads.Thisstructurecloselyparallelsthatoutlinedforenvironmentalmainstreamingmoregenerally(OECD,2012).Possibleentrypointsformainstreaminginnationalstrategicplanningpolicyindeveloping
countries
Planninglevel Entrypoint
Nationalgovernmentandcrosssectorministries
• Nationaldevelopmentvision(long-term)• Povertyreductionstrategy• Nationaldevelopmentplan(e.g.5year)• Nationalbudgetallocationprocessorreview
Sectorministries • Sectordevelopmentplans• Sectormasterplans• Sectorbudgets
Subnationalauthorities • Decentralisationplans• Districtplans• Subnationalbudgets
Source:UNDP/UNEP(2011),MainstreamingClimateChangeAdaptationintoDevelopmentPlanning:AGuideforPractitioners,UNDP-UNEPPoverty-EnvironmentInitiative,KenyaThissituationismadeslightlymorecomplicatedasmanydevelopingcountriesareproducingNationalAdaptationPlans(NAP).TheUNguidanceforthedevelopmentofNAPsoutlinestheneedformainstreamingindevelopingsuchplans-criticalbecauseofthestrongoverlapwithexistingdevelopmentactivities(LDCExpertGroup,2012a;2012b),however,mostexistinginitiativestendtobeundertakenasstand-aloneactivities.TherearenowexamplesofthepracticalimplementationofmainstreaminginsomeAfricancountries,thoughcountrieshaveadoptedarangeofapproaches.Oneroute–ormodality–istointroduceadaptationasanextensiontoexistingenvironmentalmainstreaming.Forexample,somecountriesalreadyinclude“environment”asacross-cuttingthemeintheirnationaldevelopmentvision,nationaldevelopmentplans(e.g.medium-termplans,fiveyearplansorpovertyreductionstrategies),andsectordevelopmentplans.AnexampleistheGovernmentofRwanda,whichhasintegratedclimatechange(with
13
environment)asoneofsevencross-cuttingissuesinnationaldevelopmentandsectordevelopmentplanning(RepublicofRwanda,2014).Itisevenpossibletoextendthistocaptureclimatemainstreaming,andinRwanda,theseactivitiesarebeingintegrated,oratleasttracked,inthenationalbudgetallocationprocessandinsectorbudgetactivities.Othercountrieshaveadoptedaslightlydifferentapproach,developingstand-alonesectoraladaptationaction,planswhichcomplementexistingsectordevelopmentplansandactivities.ExamplesincludeEthiopia,withitsClimateResilienceStrategyforAgriculture(FDRE,2014)andTanzania,whichhasdevelopedasectorAgricultureClimateResiliencePlan,2014–2019(GoT,2014).Thesemainstreaminginitiativesareledbytherelevantsectorministries/line-ministriesandbuildonexistingsectordevelopmentplans,butproducestand-aloneandcostedadaptationplans,becauseofthedifferentiation/opportunityforclimatefinance.Thisapproachisclearlyinfluencedbythepotentialforadditionalinternationalclimatefinance,thoughitinvolveslessdirectintegration.Movingdowntotheprogrammeandprojectlevel,existingsafeguardmechanisms,suchasenvironmentalimpactassessment(EIA),provideanaturalentry-pointforconsideringwhetherprojectsarevulnerabletoclimatechangeorcouldexacerbateclimateriskselsewhere.Althoughoriginallydesignedtopreventnegativeimpactsontheenvironment,theEIAprocesshasthebenefitofbeingafamiliarandwell-establishedpartofthepolicy-makingprocessinOECDcountries.However,itonlycapturesthosepoliciesthataresubjecttoenvironmentalimpactassessments,suchasinfrastructureconstruction.Moreover,itmayrequirerevisionofthelegalframeworktoincludeclimaterisks.Asdiscussedlater,itmayalsocometoolateintheprocesstobereallyinfluential.Moregenerally,climateriskscreeningcanbeappliedasastepinthepolicy-makingprocesstoidentifywherepolicies,programmesorprojectsmaybeparticularlyvulnerabletoclimatechange.Thishasemergedstronglyinrelationtoinvestmentprojectsfundedbytheinternationalfinanceinstitutionsandmultilateraldevelopmentbanks.Forexample,theAfricanDevelopmentBank(AfDB,2011)hasintroducedaClimateSafeguardSystemthatincludesatrafficlightsystemorscorecardtoidentifywhichprojectsmaybehighlyvulnerabletoclimateriskandrequireamoredetailedevaluationtoconsiderintegrationofclimateaspectsintodesignandimplementation.Thesetendtohaveastrongfocusonenhancingtheclimateresilienceofinfrastructureormajorinvestments.Thisdoesraiseaninterestingpointinthatthestimulusformedium-longtermdecisionsmaycomefromthedevelopmentcommunityandfromstipulationsonfinance,whichislikelytobemoreinfluentialthanwhenoriginatingfromsectorsinLDCsthemselves.Acomplementtotheidentificationofhigh-riskpolicies,projectsandprogrammesistheintegrationofadaptationintoexistingpolicyandprojectappraisalguidance.Thisentailsthemodificationofexistingappraisalguidancetoalsocoverclimatechangeortosupporttheconsiderationofsomeoftheadditionalaspectsandchallengesofadaptation.However,suchguidanceisoftenweakinsub-Saharancountries.Finally,afurtherapproachistoupdateclimatechangeallowances,ashasbeendoneforfloodsinseveralOECDcountries(WilbyandKeenan,2012):thiscanbeextendedtoupdatedesignstandards.However,cautionisneededtoensurethatthebenefitsofsuchactionsjustifytheadditionalcosts,especiallygivenfuturediscountingofuncertainbenefits
14
Inlookingattheseissues,recentstudieshavehighlightedthatmainstreamingenvironmentorclimatechangedoesinvolvemajorchallenges,notablyduetothelackofcapacity,timeandresourcesinthesectors(i.e.asclimatedecisionsmovefromtheMinistryofEnvironmentoutwards).Thesestudiesalsoprovidesomeusefulrecommendationsonhowtoaddressthesechallenges.TheOECD(2012)studyongreeningdevelopmenthighlightedspecificinterventionsincluding:usingmulti-yeardevelopmentplanningprocesses,developkeyactorstechnicalskills,encouragetheparticipationofnon-governmentactors,buildfunctionalandtechnicalskills,andplanandtargeteffortscarefully.Italsoprovidedsomerecommendationsonhowdevelopmentsupportcandeliverbettercapacity,highlighting:viewcapacitysupportfortheenvironmentasunderpinningalldevelopmentsupport,collaborateacrossdomesticagencies,harmoniseapproachesamongdevelopmentsupportproviders,nurturelocalownership,focusonresults,implementbestpracticeguidelines,andreflectandlearn.TheIDRC(OECD,2015)reviewhighlights:
• Mainstreamingwillneedtoaligntothepolicyandinstitutionallandscape,andconsiderexistingprocessesorguidance,suchasprojectcyclestepsandappraisaldocumentationalreadyinplace.
• Pragmatismisessentialasanytoolorguidanceneedtofitwiththeresource,time,capacityandexpertiseavailableforpolicyorprojectanalysts;otherwisetheywillnotgetused.
• Thestageatthedecision-makingprocesswhenadaptationisconsiderediscritical.Itisimportanttoensurethatthemainstreamingactivitiescomeearlyenoughintheprocesstoinfluencethedecision,oraretargetedatkey‘windowsofopportunity’(Ballard,2014;MoserandEkstrom,2010)whichwilloftenbenon-climaticinnature(e.g.replacementormaintenancecycles).Thismayrequirestrategicissuestobepickedupearly-on,eitherinrelationtothesectorstrategyortheoverallinvestmentportfolio(e.g.atriverbasinlevelratherthanprojectlevel).Italsomeansthatclimaterisksandmainstreamingactivitiesneedstooccurearlyintheprojectcycle,attheconceptordesignstage,andideallybealignedtoapprovalmilestones.Theinclusionofadaptationconsiderationsattheenvironmentalimpactassessmentstage,forexample,isusuallytoolatetohaveamajorinfluenceonprojectdesign.
• Itmaybeusefulfordecision-makerstoalsoidentifyopportunitiesthatcanbecreatedbyimplementingadaptation,ratherthanfocusingonlyontherisksandameliorationactions(Hallegatte,2011).
• Thepathfromidentifyingpotentialentrypointsandprovidingtoolsthroughtoimplementationischallenging.Achievingthisrequiresinvolvingadiversityofusersandstakeholders,findingrelevantchampions,buildingpartnershipsandprovidingsupportnetworksandcapacitybuilding.
15
The Economic Case for Action (or Not) Whilethesectionsaboveprovidesomegenericpriorityareas,itisimportanttolookattheeconomiccaseforactiontotesttheseassumptions.Thisisparticularlyimportantformediumandlong-termdecisionmaking,becauseoftheprofileofcostsandbenefitsovertimeforadaptationdecisions(DFID,2014).Inmanycases,themostimportantimpactsofclimatechangearelikelytoariseinthefuture,say2030andbeyond,whentheclimatesignalemerges.Withineconomicanalysis,thebenefitsofadaptingtothesechangesaccumulateoverlonger,futuretimehorizons,whilethecostsareincurrednow.Usingthepublicdiscountratesconventionallyusedindevelopingcountries(e.g.DFIDusuallyworkswitha12%discountrate–thoughfurtherdiscussiononthisispresentedlater),futureadaptationbenefitsinthemediumtermandbeyondareverysmallincurrentterms.Thiscanbeseeninthefigurebelow.A£1benefitthatarisesin2040(in25years),hasapresentvalueof£0.06andevena£1benefitin2030(in15years)apresentvalueof£0.18.
Profileofcostsandbenefitsformedium-long-termadaptation(left)andeffectofdiscounting
(right)showingthevalueofafuturebenefit(inyearsfrom2014to2040)whendiscounted
backtoacurrentpresentvalue
Source:FCFA,2014:DFID,2014Toshowhowdramatictheeffectofdiscountingreallyis,particularlyindevelopingcountries,asimpleexampleisprovidedbelow.Westartwithanupfrontadaptationcostof£1inyear0,andcomparethistoastreamoffutureadaptationbenefits.Theseadaptationbenefitsstartin2035(in20years),anddeliverabenefitof£0.1/year,continuingatthisleveloverthenext30years.Thetotalundiscountedbenefitsaretherefore£3(comparedtotheup-frontcostof£1).However,thesefuturebenefitsneedtobediscounted:usingconventionalUKdecliningdiscountrates(startingat3.5%),thediscountedstreamofbenefitsisapproximately£1,thusthecostsandbenefitsarebroadlyequal(i.e.thebenefit:costratioisapprox.1).ThishighdeclinehappensbecausethediscountratesItime-invariant,implyingexponentialreductions.
16
Profileofcostsandbenefitsformedium-long-termadaptation,comparing£1in2015
(adaptationcosts)withatotalstreamofadaptationbenefitsof£3(2035–2065),whichafter
discountingat3.5%decliningalsoequal~£1inpresentvalueterms(approx.BCR=1).
However,ifthissameexampleisconsideredinthedevelopingcountrycontext,usingatypicaldiscountrateof12%,thepicturechangesdramatically.Infacttheannualbenefitstreamof£3(undiscounted),dropsbyanorderofmagnitude,toapproximately£0.1,thusthebenefit:costratiois~0.1,whichishighlyunattractive.Thecorollaryofthisisthattogetabenefit:costratioofapproximately1inadevelopingcountry,theannualbenefitstreamhastoincreasebyanorderofmagnitude,i.e.anupfrontadaptationcostof£1onlymakeseconomicsenseiftheannualstreamofbenefitsare£1/year,startingin2035andextendingcontinuallyfor30years.Incredibly,thismeansthatatotaladaptationbenefitof£30,afterdiscountingat12%,equatestoonlyapproximately£1inpresentvalueterms.AnalysisoftheECONADAPTinventory(onadaptationcostsandbenefits)showsthatthislevelofbenefitstocostsisfairlyunprecedented.TherearesomeexamplesofundiscountedbenefittocostratiosthatarethishighforearlyDRRoptions,andforlong-termcoastalprotection,buttheseareexceptions.Inpracticalterms,thismeansthatthelimitedresourcesavailableinsuchcountriesarebetteroffspentelsewhere(i.e.togivehighersocialbenefit)andgivesgreaterpreferencetolow-andno-regretoptionsastheseproduceimmediateeconomicbenefits.However,theremaybesomecaseswheremediumtolong-terminvestmentscanbejustified,andthestudyhasexaminedthesewithsomesimpleexamples/schematics.Theyareoutlinedbelowanddrawonsomeofthelow-regret,value-for-moneyanalysisidentifiedintheDFIDstudy(2014)formainstreamingandaddressinglong-termchallenges.ThecostsofresilienceareverylowEarlystudies(seeAgrawalaandFankhauser:OECD,2008)estimatedthecostsofadaptationusinganinvestmentandfinancialflowanalysismethod.Thisappliesanadaptationcost“mark-upˮtofutureinvestmentplanstotakeaccountoffutureclimatechange,usuallyaround10%(forexample,theWorldBank(2006)estimatedthataccountingforfutureclimateinhigh-riskprojectstodaycouldpotentiallyincreaseprojectcostsbybetween5%and15%).Inpracticalterms,thismeansthatifadaptationincreasesthecostsofaprojectby10%,thenthebenefits
17
thatitproducesneedtobegreaterthan100%andoccurineachyear,iftheystartinthefuture,atleastfora12%discountrate(seeabove).However,ifthecostsofadaptationareverylow,thentheremaystillbeajustificationforearlyaction.Forexample,ifthecostsofadaptationare1%oftheprojectcosts(or£0.1intheschematicabove),anddeliverfuturebenefits(£0.1peryear,totalling£3undiscounted,andjustunder£1discounted,thusapproximatelyaBCRof~1),thentheinvestmentmaymakesense.Ofcourse,theactualratioofprojectcostsandfuturebenefitswillvaryonacasebycasebasis,butthisillustratesthatifverylowcostover-designispossible,thenthismightbeworthconsidering,evenunderconditionsofhighdiscountrates(thoughperhapsnotunderconditionsofhighfutureuncertainty).Thefutureimpactsofclimatechangeareveryhigh(shocksandindirecteffects)Reversingthelogicabove,therewillalsobeacaseforadaptationwhenthefutureadaptationbenefitsareveryhigh.Thismayariseforanumberofreasons.First,whentheimpactsofclimatechange,andthusthepotentialbenefitsofadaptationintermsofavoideddamages,areverylarge.Thismayarisefromlargeshocks(naturalhazards).Majorextremes,suchasmajorfloods,tropicalstorms,ormajordroughts,alreadyleadtohigheconomiccosts(IPCC,2012),andchangesinthefrequencyandintensityofmajoreventscouldleadtolargefuturedamagecosts.Inturn,thebenefitsofdisasterriskreductioncouldbeverylarge.Ifthereisanexistinghighadaptationdeficit,notingtheseeventsareprobabilisticinnature,earlyactionwillhavebenefitsinreducingtherisksofearlydamage.However,thisisalow-regretoption,i.e.thisissomethingthatshouldbedoneanywayandthereforenotdirectlyrelevanttothe10–40yearlifetimeofinterest.TheissuethereforeiswhetherthechangeinrisksassociatedwithclimatechangeshouldbeaccountedforinearlyDRRactions,i.e.whethercoastalorriverflooddikesshouldbebuilthighertotakeaccountofchangesinstorm-surgeorfloodintensity.Itisthereforethemarginalcosts–andthemarginalbenefits–toaddressfuturerisks,whichisimportanthere(notingthisgetsverycomplicatedveryquickly,becauseitdependsontheassumptionsofreturnperiods).Whatisclearisthatusingthesimplifiedschematicabove,themarginalcostsoftheseadditionalevents(ortheirextraintensity)needstobeverylargetojustifyadditionalearlycosts.Thefigurebelowassumesthatalargeeventoccurseverytenyears,startingin20years.Ifthisleadstolargedamagecosts–andbyassociationlargeadaptationbenefits(shownasanadaptationbenefitof£10everytenyear,discountedat12%)–thenthispassesaCBAtest.However,whatisinterestingisthatitisonlythefirsteventthatjustifiestheearlycosts(thisalonehasabenefittocostratioof1):whereasverylargefutureeventsgetdiscountedveryheavily(ascanbeseenbythedecliningpresentvalueoffutureevents).Asabove,adaptationmayreducebutnoteliminatetheeffectsoftheseevents,andtheseeventsareprobabilisticaswellasuncertain,sotheymaynotmaterialise.
18
Profileofcostsandbenefitsforlong-termadaptation,investigatingfutureshockandhigh
futureadaptationbenefits.
Asecondcaseariseswhenthereareindirecteffects.Usingfloodsasanexample,thiswouldincludedirecteffects(e.g.buildingdamage),directintangibleimpacts(e.g.lossoflife,damagetoecosystems),indirecteffects(disruptiontotransportorelectricity)andindirectintangibleeffects(e.g.effectsonwell-beingfrompostdisasterstress).Thishasclearoverlapwiththeextremesabove,butofmostrelevance,itcouldapplycriticalinfrastructure.Infrastructureisdeemedcriticalifitsfailurethreatensthesafety,economy,lifestyleandpublichealthofacity,aregion,orevenastate.Thesecriticalinfrastructuresarespecificinthattheygobeyondgeographical,political,culturalandorganisationalboundaries(Boin&McConnell,2007).TheWorldBank(2011)hashighlightedpreviouslythatcriticalinfrastructureisapriorityforfutureproofing.Ifduringanevent,criticalinfrastructureisdestroyed(e.g.watersupplysystems,watertreatment,healthcareinfrastructure,etc.),thiswillleadtolargerindirecteffectsincludingintangibleeffects.Forthisreason,thereislikelytobeastrongereconomiccaseforover-protectingcriticalinfrastructure,ineconomicaswellassocialandhealthterms.FuturebenefitsstartnowandbuildupovertimeAfurthercasewhereearlyactionmightbejustifiediswhentherearesomeearlybenefitsofearlyadaptationaction,evenifthesearenotsufficienttojustifyinvestmentontheirown.Twofiguresareshownbelowtoillustratethis.Thefirstassumesanadaptationcostof£1inyear0.Itthencomparesthistoabenefitstreamstartingin2035of£0.1/year,continuingfor30years(£3).Afterdiscountingat12%,thestreamoffuturebenefitsonlytotals~£0.1,thusfailsacost-benefitanalysis(BCR~0.1).However,ifearlybenefitsarefactoredin,thingsimprovesignificantly.Ifweassumeadaptationbenefitsstartinyear1,at£0.1/year,andcontinueatthislevelovertime,thenthepresentvalueofbenefitsincreasestojustunder£1afterdiscounting(at12%),thusanapproximateBCRof~1.Thisdoesrunintosomeproblems,notablythereneedtobeearlyrobustclimatetrendswhichcangeneratethesebenefits,anditisafinelineastowhethermostoftheseoptionswillbeearlylow-regretmeasures.Furthermore,thedeliveryofbenefitsinthefirstfewyearsiscritical,astheseprovidethelargestdiscountedbenefits.
19
Profileofcostsandbenefitsformedium-long-termadaptation,comparing£1in2015
(adaptationcosts)withatotalstreamofadaptationbenefitsof£3(2035–2065),whichafter
discountingat12%decliningequalsapprox..£1inpresentvalueterms(BCR=~0.1).
Profileofcostsandbenefitsforadaptation,comparing£1in2015(adaptationcosts)witha
totalstreamofadaptationbenefitsof£5(2015–2065),whichafterdiscountingat12%
decliningequalsapprox..£1inpresentvalueterms(BCR=1).
DifferentassumptionsaremadeondiscountratesClearlyoneofthesimplestwaystoincreasetheattractivenessoflong-termadaptationistochangetheassumptions–providedthiscanbejustified.Ascanbeseenfromthefirstexample,thediscountrateneedstodropsignificantlytomakeadifferenceforlong-termbenefits,i.e.towardstheratesusedinOECDcountries.However,giventheextremelyhighimpactofdiscountingat12%,evenmodestreductionsindiscountratecanmakealargedifference–thefigurebelowshowstheimpactofreducingrates.
20
DiscountinginUKPublicPolicyAppraisal
HMT(2007)recommendsaSocialTimePreferenceRate(STPR)forpublicpolicyappraisal,derivedfromtheequationρ+μ.g,basedontheRamseydiscountingformula,where:ρ=therateatwhichindividualsdiscountfutureconsumptionoverpresentconsumption,whichiscombinedwith• theproductoftheannualgrowthinpercapitaconsumption(g)and• theelasticityofmarginalutilityofconsumption(μ)withrespecttoutility,reflectingthefactthat
ifpercapitaconsumptionisexpectedtogrowovertime,thiswillimplyfutureconsumptionwillbeplentifulrelativetothecurrentpositionandthushavelowermarginalutility.
ρitselfcomprisesoftwoelements:• Catastropherisk(L);and• Puretimepreference(δ).Catastropheriskisthelikelihoodthattherewillbesomeeventsodevastatingthatallreturnsfrompolicies,programmesorprojectsareeliminated,oratleastradicallyandunpredictablyaltered.Examplesaretechnologicaladvancementsthatleadtoprematureobsolescence,ornaturaldisasters,majorwars.Thepuretimepreference,reflectsindividuals’preferenceforconsumptionnow,ratherthanlater,withanunchanginglevelofconsumptionpercapitaovertime.HMT(2007)reportsthattheevidenceindicatesavalueforρofaround1.5percentayearforthenearfuture,anannualrateofgat2percentperyear,andanelasticityofthemarginalutilityofconsumption(μ)ofaround1.Thereforewithg=2percent,ρ=1.5percent,μ=1.0,thentherealdiscountrateis0.015+1.0*0.02=3.5percent.Whyuse10-12%indevelopingcountries?
Intheory,asimilarUKsocialdiscountformulacanbeappliedindevelopingcountries,thoughclearlyρismuchhigher(becausetheyarepoorerandbecausegrowthratesandfutureincomesarehigher).ThisleadstohigherdiscountratesthanusedintheOECD(notingOECDratesaretypically3to6%).However,theconventionistousesocialdiscountratesof10-12%indevelopingcountries,whichimpliesratesthatarehigherthanwouldarisefromtheuseoftheRamseyformulaabove.Inpractice,theseratesarebasedonalternativeapproachesforderivingthesocialdiscountrate.AgoodreviewofpracticeisincludedintheADBreviewofZhuangetal.,2007).Insummary,aswellastheuseoftheRamseyformula,ZhuangalsocitesexamplesoftheempiricalestimationofSRTP.TheyalsoreportontheuseoftheMarginalSocialOpportunityCostofCapitalforestimatingsocialdiscountrates.Thisarguesthatresourcesinanyeconomyarescarce,thatgovernmentandprivatesectorcompeteforthesamepooloffunds;thatpublicinvestmentdisplacesprivateinvestment,andthusthatpublicinvestmentshouldyieldatleastthesamereturnasprivateinvestment.Afurtheralternativeistouseaweightedaverageapproach,toreconciletheSRTPapproachwiththatofSOC,andafurthervariationofthis,usingtheshadowpriceofcapital(SPC).Zhuangetal.,2007alsosummarisediscountratesinuse,notingthatvariouscountriesuseSTRPorSOCapproaches(thelattergenerallyleadingtohigherrates).Ingeneral,thereviewfoundmoreuseofSTRPindevelopedcountriesandmoreuseofSOCindevelopingcountries(e.g.IndiaandPakistanuse12%(SOC)),thoughwithsomeuseofweighedaveragesinMDBs.
21
However,amorepracticalreview,focusedondevelopmentpartnersandinternational/multi-lateralfinanceorganizations,aspartofthisstudy,revealsthatratesareoftennotbasedonastrongeconomicrationale.TheWorldBankpublishedaHandbookonEconomicEvaluationofInvestmentOperations(Bellietal,1997),onpage127,itsays:"[...]Thediscountrateusedshouldreflectnotonlythelikelyreturnsoffundsintheirbestrelevantalternativeuse(i.e.,theopportunitycostofcapitalor“investmentrateofinterest”),butalsothemarginalrateatwhichsaversarewillingtosaveinthecountry(i.e.,therateatwhichthevalueofconsumptionfallsovertime,or“consumptionrateofinterest”).TheBanktraditionallyhasnotcalculatedadiscountratebuthasused10-12percentasanotionalfigureforevaluatingBank–financedprojects.Thisnotionalfigureisnotnecessarilytheopportunitycostofcapitalinborrowercountries,butismoreproperlyviewedasarationingdeviceforWorldBankfunds.Taskmanagersmayuseadifferentdiscountrate,aslongasdeparturesfromthe10-12percentratehavebeenjustifiedintheCountryAssistanceStrategy.TheADBfollowstheWBandadoptsthesameapproach.ADBGuidelinesstatesthatbecauseitistoodifficulttopreciselyestimatetheopportunitycostofcapitalineachcountry,10-12%isused.seepage37http://www.adb.org/sites/default/files/institutional-document/32256/eco-analysis-projects.pdfSources:HMT(2007);WorldBank(2007),ADB[Zhuangetal]2007.Therearesomepotentialreasonswhyalowerdiscountratemightbeused.Applyinghighdiscountratestocountriesinthefuturemaybebiased,astheirfuturegrowthwillslowwithdevelopment,anduncertaintyandcatastropheriskwillalsofall.Thereisadiscussionwhetherclimatechangeitselfmightreducefuturegrowth,whichwouldimplytheuseoflowerordecliningdiscountratesforadaptation.Afurthersetofadjustmentscanbeintroduced,decliningrates(HMT,2003)[hyperbolicdiscounting]orintergenerationaldiscountrates(HMT,2009).Thedecliningrate(intheUK)isusedbecauseofuncertaintyaboutthefuturevaluesoftimepreferenceandcalculatesacertaintyequivalentratetakingintoaccounttherangeofthisuncertainty.However,becausethereducedratesdonotkick-inuntilyear31,seetheschedulesbelowforthestandarddecliningandintergenerationaldecliningschemes,thiswillnotmakemuchdifferencetoadevelopingcountrycontextthatstartswithahighdiscountrate(becausethemaineffectofdiscountingwillhavealreadyoccurred).OfcourseintheUKorOECDcontext,wherelowersocialdiscountratesareused,theseschemesdomakeadifference.Theuseofintergenerationalratereflectsthefactthatdiscountingcanleadtoperverseoutcomes,especiallywherepotentialcatastrophicconsequencesoccurinthefuture,evenifthesecanbeavoidedwithsmallearlyinvestment(i.e.theendoftheworldbecomesoptimal).Thisisaparticularissueforclimatechangemitigation.AshighlightedbyWeitzman(2009),withclimatechange,thereisthepotentialforplausible,ifunknown,catastrophicclimatechangeandsocalled‘fattails’,wherethetailsofthedistributiondominateandtheexpectedwelfarelossispotentiallyunbounded(e.g.duetomassspeciesextinctionandbiosphereecosystemdisintegration).Theconsiderationoftheseextremeoutcomesleadstoradicallydifferentconclusionsfromtheconventionalstandardeconomicanalysisandformalizedcostbenefitanalysis.
22
Thereisastrongeconomicjustificationforavoidingtheseextremeoutcomes(Sternetal,2006)andtheSternrevieweffectivelyuseda0.1%valueofρintheRamseyformulaabove,duetothecatastrophicrisk–leadingtolowrates,thoughitstilldiscountedforgrowth.HMT(2009)introducedadiscountingschemetotakeaccountofintergenerationalissues,i.e.irreversiblewealthtransfersfromthefuturetothepresent.ThisisdifferenttotheSternschemeandisshownbelow.
SourceHMT,2008.Again,suchanadjustmentmaynotmakeasmuchdifferenceintheLDCcontext,becausethisisafairlylowcomponentoftheoverallsocialdiscountrate.Indevelopingcountries,thegrowthcomponentofthediscountrateismuchhigher,thuschangesinρarelesslikelytoimpactonthefinalrate.OptionvaluesandthevalueofinformationareincludedRealoptionsanalysis(ROA)quantifiestheinvestmentriskwithuncertainfutureoutcomes.Itisparticularlyusefulwhenconsideringthevalueofflexibilitywithrespecttothetimingofcapitalinvestment,oradjustmentofthesizeandnatureofinvestmentoveranumberofstagesinresponsetounfoldingevents.Intheadaptationcontext,thisallowsfortheanalysisofflexibility,learningandfutureinformation,particularlyrelevantforuncertainty(McDonaldandSiegel,1986;DixitandPindyck,1994).Itisparticularlyusefulwhenconsideringthevalueofflexibilitywithrespecttothetimingofcapitalinvestment,oradjustmentofthesizeandnatureofinvestmentoveranumberofstagesinresponsetounfoldingevents.Intheadaptationcontext,thisallowsfortheanalysisofflexibility,learningandfutureinformation,particularlyrelevantforuncertainty(Watkissetal,2014).ROAtypicallygivestwotypesofresultthatsetitapartfromconventionaleconomicanalysis.Thefirstappliestoprojectsthatarecost-efficientunderadeterministicanalysis:ROAmayshowthatitmakesmoresensetowaitfortheoutcomeofnewinformation,ratherthaninvestingimmediately,ifthebenefitsofthenewinformationoutweighthecosts–i.e.deferredbenefits–ofdelayingimplementation.Thevalueofwaitingwillthenbehigherifthedegreeofuncertaintyregardingthereturnoftheprojectisgreater;andthedurationoftheperiodofwaitingbeforeinformationisgainedisshorter.Thevalueofwaitingneedstobebalancedagainstthecostofwaiting,becausewhilewaiting,theprojectwillnotbedeliveringbenefits.ThesecondappliestoprojectswhichfailaconventionalCBAunderdeterministicanalysis,butunderconditionsofuncertaintyitmaymakefinancialsensetostarttheinitialstages,oratleast
23
keeptheoptionopenforpotentialfutureinvestment.ThisarisesbecauseROAhelpsunderstandhowprojectvalueevolvesduringdevelopment:therewilloftenbeflexibilitytoadjusttheprojectasitproceedsanditcanexpand,contractorstop.ROAcanincorporatethisvalueofflexibility(whichisomittedinstandardeconomicanalysis).AswithCBA,effectivetreatmentofriskpreferencesdependsontheabilityoftheanalysttodescribetheseaccurately.However,asROAdependsonexpectedvalueswithinaconventionaleconomicframework,thediscountingissuesindevelopingcountrieswillstillarise.Indeed,thepenaltyofwaitinganddeferringearlyprojectbenefitsincountriesexperiencinghighGDPgrowthwillbehigh.Other(sustainability)argumentsareintroducedAfurthersetofliteraturehighlightsthatwhileeconomics(andtheuseofdiscounting)reflectspreferences,thiscanresultinsomewhatstrangeoutcomes(e.g.asinthemitigationdomain,wherethe‘endoftheworld’canbecomeoptimal).Anumberofdifferentargumentshavethereforebeenadvancedtohighlightkeyproblems,ortoincludeextracriteriaoradjustmentsthatshouldbemadetostandardCBA.Asanexample,Annandale(2013)presentsacaseonlargehydropowersitesinthecontextofalimitednumberofsuitablesites.Hehighlightsthatthesesitesareaffectedbysedimentation,whichreducesstoragecapacity.Currenteconomicanalysisdoesnottakeaccountofthecostsofloststorage,becauseitisdiscountedheavilyasitoccursinthefutureaftermanyyears.Asaresult,ongoingsedimentationmanagementapproachesdonotappearfavour.However,thisthenleadstohighlevelsofsiltationthatrenderthesitesunusablewithoutmajorsedimentationremoval.Asaresult,heraisestheprincipleofhotelling,i.e.thatthevalueofanexhaustibleresourceincreaseswiththediscountrate(i.e.discountedvaluedoesnotchange),thoughtheeconomiccaseforthisisnotstrong(indeedabetterapproachmightbetouserealoptionsanalysis,seeabove).
Discussion Drawingonthesectionsabove,thekeyareasidentifiedformediumandlong-termplanningareoutlinedbelow,splitintotypeII(short-termdecisionswithalonglife-time)andtypeIII(addressingfuturechallenges).Theprioritiesinclude:• Criticalinfrastructure,becauseofrolepostdisaster(notingfailureduringmajorclimate
shockswillleadtohighindirectlosses).Thiscouldincludebridgesascriticalnodesforsimilarreasons,andbecauseofthelargelyirreversiblenature.
• Largehydropower(orwaterstorage),notingthisisaffectedbychangingtrendsbecauseoftheongoingoperationalcostsoflowergenerationorunmetdemandindrierscenarios,aswellasdamagefromheavyprecipitationextremes.
• Urbanland-useplanning,duetothelonglife-timeofspatialdecisions,andthepotentialexposuretofutureextremes(andindirectcosts).
• Agriculturalland-useplanninganddevelopment,especiallycoffeeandtea,forestrymanagement,duetothelonglife-timesinvolved.
• Infrastructure–ifthereisopportunityforlowcostover-design,flexibilityorrobustness.
24
• Anumberofmajorfuturemajoreffects,wheresomeearlyiterativeplanningiswarrantedbecauseofirreversibilityandhighratesofchange/lowadaptivecapacity.
Theseformpossibleareastoexploreinthecasestudiesinphase2.
Capital Investments What’stheissue?Inputtingtogetheraconceptualframeworkforidentifyingdecisionstodaythataffectclimatevulnerabilityinthelongtermandthatshouldtakefutureclimaticconditionsintoaccount,itisimportanttobeawareofratesofdepreciationonthesortsofcapitalinvestmentinvolved.Whilesomecapitalinvestmentstodaymightappearvulnerabletofutureclimateortootherwiseaffectvulnerabilitytoclimatechange,theresultingcapitalstockmaydepreciatesofastthatitseconomiclifetimeisrelativelyshort,saynotmorethanadecadeortwo,whereincurrentclimatevariabilityisthedominantfactorinitsperformance.
25
CapitaldepreciationinAfricaCapitaldepreciationisarelativelyunder-researchedissue.Inthevastmajorityofstudies,therateofdepreciationissimplyassumedandmoreoverthesamerateisassumedtoapplytodifferentcountries.Typicalassumptionsfortheaggregatecapitalstockareinarangefromabout7%(Easterly&Rebelo1993)toabout10%(Nordhaus&Sztorc2013),whichimpliesthat,overthecourseofitsfirstdecadeinuse,thevalueofarepresentativeassetfallsby52-65%andafter20yearsitdoessoby67-88%.However,therearereasonstobelievethatratesofcapitaldepreciationarenotuniformacrosscountriesandinparticularthattheremaybesystematicdifferencesbetweencountriesbasedontheirlevelofdevelopment.Intheory,thedisparitycouldgoeitherway:
• Capitaldepreciationinlower-incomecountriessuchasthoseinAfricacouldbelowerthaninhigh-incomecountries,ifalargeproportionofinvestmentisinusedratherthannewgoods,usedgoodsdepreciatingmoreslowly.
• Ontheotherhand,ittendstobeassumedthat,ifthereisadifference,itisthatcapitalinlower-incomecountriesdepreciatesfaster.Thereareseveralcandidateexplanationsforthis,includingfinancialconstraintsthatleadinvestorstopurchaselessdurableinvestmentgoods(Udryetal.2006),andinparticulararangeofmechanismsthatultimatelyresultinunder-maintenanceofcapitalassets,includingthatthegoodsareimportedfromhigh-incomecountriesandareunsuitableforlocalconditions,corruption(Davoodi&Tanzi1997),anticipatedcapitalunder-utilisation(whichmakesitefficienttodolessmaintenance),highratesoftimepreference,andmarketdistortionsthatmakescapitalinvestmentartificiallycheap.
Therehavebeentworecentstudiesestimatingcapitaldepreciationratesindevelopingcountries,bothfocusingonthemanufacturingsector.Schuendeln(2013)analysessurveydataforIndonesianfirmsandestimatesdepreciationratesbetween8%forasimplestatisticalmodeland14%foramodelwithmoreconvincingcontrols.Largerandyoungerfirmshadhigherdepreciationrates,whichmayindicatetheyusenewerequipment.AmoredirectlyrelevantstudyisBu(2006),whoanalysedsurveydatafrommanufacturingfirmsinsevendevelopingcountriesincludingfourcountriesinSub-SaharanAfrica(Coted’Ivoire,Ghana,KenyaandZimbabwe).Thedataarerathernoisy,so,usingthemedianfirmasthemeasureofcentraltendency,depreciationratesintheAfricancountriesvariedfrom17%to62%acrosscountriesandusingdifferentmethodsofaccountingforinflation.Thisstudyalsolooksatdepreciationratesfordifferentkindsofasset,findingthatdepreciationislowerforbuildingsandhigherformachineryandequipment,asonemightexpect.Overall,BuconcludesonthebasisoftheevidencethatcapitaldepreciatesfasterindevelopingcountriesandtheevidenceinSchuendelnmightalsobetakenas(somewhatequivocal)supportforthis.Usefullifeoffixedassets
26
Inadditiontostudiesonthedepreciationrateofthecapitalstockinaggregate,researchhasexaminedthedepreciationratesofindividualassetclasses.Thesestudies,inturn,informtaxcodes.CountriessuchastheUSprovidestandardassetlivestobeusedincalculationsofcorporatetaxliabilitiesforawidevarietyofassetclasses,manyofwhicharerelevantforthisstudy.Unfortunately,studiesonthedepreciationratesofparticularassetclassesindevelopingcountries,andinAfricainparticular,arerare.Taxcodestendtodistinguishbetweenmanyfewerclassesofassets,ifguidanceonusefullivesisprovidedatall.Inaddition,thereisoftennoevidencethatthejudgementsonusefullivesprovidedwithintaxcodesarebasedonrigorousresearchonthedepreciationrateofassets.Table1providestheusefullifeoffixedassetsasestimatedbytheBureauofEconomicAnalysis,basedintheUnitedStates,andusefullivesforequivalentassetsasrecommendedbytheIRSforuseincalculatingtaxliabilities.FortheBEAdata,wherepossible,depreciationrateshavebeenestimatedusingassetpricesintheresalemarket.Wherenodirectdatawereavailable,therateshavebeenbasedonavarietyofsources,including‘theresearchofBEA,DaleJorgenson,theBureauofLaborStatistics,andJackFaucettAssociates,aswellastheirownjudgementtodeterminethegeometricrateofdepreciationonacasebycasebasis’.ThemethodologyusedbytheIRSislesstransparent,butaslightlybroaderrangeofassetsappearstobecovered.Theusefullivesreportedineachofthetwosourcesarebroadlyconsistent.Ascanbeseen,mostoftheassetsconsideredofrelevanceinthisprojectappeartohaveusefullivesbetween30and50years.EvenifdepreciationintheAfricancontextissignificantlyfasterthanintheUS,thissuggeststhatdecisionsonassetstakenoverthenextfewyearswilldeterminethecharacterofcapitalstockforthenextcoupleofdecades,atleast.Depreciationrateandusefullifeoffixedassets,BEA
Sector Assettype(BEA) Usefullife
(years,BEA)Assettype(IRS) Usefullife
(years,IRS)
Energyandcommunicationsinfrastructure
Communicationstructures
40 Telephonedistributionplant
24
Electricaltransmission,distributionandindustrialapparatus
33 Electricpowergeneratinganddistributingsystems
19
Electriclightandpowerstructures
45 Electricutilitysteamproductionplant
28
Electricutilityhydraulicpowerplant
50
Urbanplanning,infrastructureandreconstruction
Sewageandwastedisposal
40 Municipalwastewatertreatmentplant
24
Municipalsewer 50 Residentialrentalproperty 27.5
Watersupply Watersupply 40 Waterutilities 50Transportinfrastructure
Railroadequipment
28 Railroadstructures 30
Railroadreplacement
38 Railroadtrack 10
27
Sector Assettype(BEA) Usefullife
(years,BEA)Assettype(IRS) Usefullife
(years,IRS)
trackAirtransportationstructures
38
Highwayandconservationanddevelopmentstructures
40
Publicbuildings Medicalbuildings 36 Non-residentialrealproperty
39
Educationalbuildings
48
Source: http://www.bea.gov/national/pdf/BEA_depreciation_rates.pdf,http://www.irs.gov/pub/irs-pdf/p946.pdf
Quantitative assessment of decisions that lock in climate vulnerability IntroductionandmethodsPreviousworkhasgivenususefulframeworksforidentifyingwhatkindsofdecision,beingmadetoday,arelikelytorequireconsiderationoffutureclimateintheirdesignandimplementation.Thesearedecisionsthat:
1. Affectclimatevulnerability(eithertheperformanceoftheprojectitselfisvulnerabletoclimate,orprojectoutcomesmorebroadlyaffectvulnerabilitytoclimate);
2. Dosointhelongrun(10yearsormore);3. Arequasi-irreversible;4. Arelargeenoughtomeritattentionfromdevelopmentorganisations.
Ranger,HarveyandGarbett-Shiels(2014)analysed250developmentprojectsfromtheWorldBankandDFIDinthreecountriesandidentifiedthetypesofprojectmost‘urgent’accordingtocriteriasimilartothoseabove.Innoparticularordertheyare:2
• Energyandcommunicationsinfrastructure;• Urbanplanning,infrastructureandreconstruction;• Watersupplyinfrastructure;• Transportinfrastructure;• Majorhydropower;• Majorirrigationinfrastructure;• Publicbuildings(schools,hospitals);• Naturalresourcemanagement.
However,welackaquantitativeunderstandingofwherethesekindsofinvestmentdecisionsarelikelytobemadeinSub-SaharanAfricainthecomingyears.Wherearethehotspots,whichwouldconsequentlybedeservingofspecialattention?
2 Weather-riskinsuranceandsocialsafetynetprogrammesarementionedinthispaper,thoughnotincludedinthelist.
28
Thissectionseekstoidentifypotentialhotspotsforinfrastructureinvestmentthataffectsclimatevulnerabilityandthatrequiresconsiderationoffutureclimateindesignandimplementationtoday.ItdoessousingaseriesofquantitativeindicatorsthatarecomparableonanationalbasisacrossthewholeSub-SaharanAfricanregion,obtainedfromarangeofinternationaldatabases.Itisnottobeconfusedwithquantitativeanalysisofclimatevulnerability(e.g.Barr,Fankhauser,&Hamilton,2010;Yoheetal.,2006).Suchanalysisisconcernednotwithdecision-makingandinvestmentperse,butwiththeoutcomesforclimatevulnerability.Thereforethefocusinthesestudiesisonmeasuresofexposure/impactsuchasdamagetocropyields,measuresofsensitivitysuchasfoodimportdependency,andmeasuresofadaptivecapacitysuchasgovernanceindices.Theprincipalmethodologicalproblemconfrontedindoingaregional,comparativeanalysisofinfrastructureinvestmentisthatsuitable,directdatadonotingeneralexist.Thereforeindirectproxiesmustbereliedupon.Forsomeoftheabovecategoriesofinfrastructure,goodproxiesdoexist.Forinstance,projectionscanbeobtainedfromUNDESAofpopulationgrowthincitiesinSub-SaharanAfrica,whichisstronglyindicativeoflikelyfutureurbanplanningandinfrastructureinvestment.Suchdataareincludedinthisanalysis.Yetforthemostpartthisisnotthecaseandreliancemustbeplacedonmoreindirectproxies.Tothisendwerelycentrallyonthenotionofinfrastructuredeficits(Yepesetal.,2008)orinfrastructureintensitygaps,inordertoquantifythepotentialforfutureinvestment.Thejustificationfordoingsoliesintheempiricallydemonstratedphenomenonofconvergenceofeconomiesalongagrowthpath(e.g.Barro&Sala-i-Martin,2004).Economiesthatstartfurtherbehindgraduallycatchupwiththeleadersintermsnotonlyofultimatelivingstandards,butalsocapitalorinfrastructureintensity:theygrowfasteronthesedimensions.Theimplicationisthatthosecountrieswithalargegaprelativetoaleading,benchmarkcountryinasuitablynormalisedmeasureofinfrastructure(i.e.infrastructureintensity)havethepotentialtoseemostinvestmentinthefuture.Theanalysisthatfollowscalculatesandpresentsresultsforarangeofmeasuresofinfrastructureintensitycorrespondingtothevariouscategoriesofinfrastructureaffectingfutureclimatevulnerabilitymentionedabove.Intensityiscalculatedindifferentwaysdependingonthecategoryofinfrastructure.Forexample:
• Theslumpopulationmaybenormalisedbythetotalurbanpopulation.Countrieswiththelargestshareofslum-dwellershavethegreatestneedofurbanplanningandinfrastructureinvestmenttoprovideadequateconditionsforsuchpeopleandthegreatestpotentialaccordingtotheconvergencestory.
• Theareaofagriculturallandthatisequippedforirrigationmaybenormalisedbytheestimatedareaoftotalirrigablelandtoshowwherethereispotentialforinvestmentinfurtherirrigation.
Thebenchmarkcountrythatischosenfortheanalysisisthedevelopingcountry,anywhereintheworld,withthehighestinfrastructureintensityinaparticularcategory.AnalternativewouldbetobenchmarkagainsttheleadingcountryinSub-SaharanAfrica,but,insofarasanabsolute,cardinalinterpretationcanbegiventothedata,doingsowouldnotconveythepotentialfor
29
furtherinvestmentevenintheleadingcountry.Regardless,apotentialweaknessisthatthebenchmarkcountrymayhaveuniquecharacteristics,whichmakeitespeciallyinfrastructure-intensive.Weaccountforthiswherepossible(forexample,verysmallcountriesareexcludedfrombenchmarkingwithrespecttopavedroaddensity),butfurtherworkcouldbecarriedouttoexcludeoutliers.Eachofourindicatorsisnormalisedbyanunderlyingabsolutevariabletoensurethattheyarecomparableacrosscountries.Tocalculatewhatlevelofinvestmentwouldberequiredtocloseaninfrastructureintensitygap,thegapismultipliedbythecurrentvalueoftheunderlyingabsolutevariabletoarriveatanabsolutelevelofinvestment.Forexample,theinpublicspendingoneducationasapercentageofGDPismultipliedbycurrentGDPtoarriveattheabsoluteadditionallevelofspendingrequiredtoclosethegap.Formostoftheindicators,forecastsoftheunderlyingvariablearethenmultipliedbytheinfrastructureintensitybenchmarkinordertoestimatewhatinvestmentwouldberequiredtomaintaininfrastructureintensityatthebenchmarklevel.Thelatestavailableforecastsareusedforeachunderlyingvariable.Thisisnotpossibleforsomeunderlyingvariablessuchasirrigablelandorpotentialforhydropowerproductionastheyareconstantovertimeorforecastsareunavailable.Unlessotherwisestated,theresultspresentedinthisanalysisarethesumoftheinvestmentrequiredtofirst,closethecurrentinfrastructureintensitygapandsecond,maintainthebenchmarkintensityinthefuture.Thisabsolutelevelofinvestmentisthenstandardisedbythetotalrangeofinvestmentneedsforeachindicatorsothateachcountryisassignedavaluebetween0and1.Ofcoursecountriesdonotalwaysneatlyfollowaprocessofconvergence.Theexistenceofaninfrastructure-intensitygapdoesnotautomaticallyimplythatthegapwillbeclosed;itmayexistforagoodreasonsuchasweakgovernance.Toaccountforthis,wepresenttwofurthersetsofresults.First,infrastructureintensitygapscanbecalculatednotwithrespecttotheleadingcountryineachcategory,butwithrespecttowhateachcountrymightbeexpectedtohaveachieved,givenitslevelofdevelopmentandothernationalcharacteristics.Inparticular,Yepesetal.(2008)carryoutaneconometricanalysisofthedeterminantsofvariouskindsofinfrastructureintensityindevelopingcountries,showingthattheydependamongotherthingsonnationalincomepercapitaandpopulationdensity.Weusethestatisticalestimatesfromthisworktoprovideapredictionofwhatdegreeofinfrastructureintensityacountrywouldhave,giventheaverageeffectofnationalcharacteristicssuchasincomepercapitaoninfrastructureintensityacrossalldevelopingcountries.Ifagapexists,thenitisnotexplainedbythesecharacteristicsanditmightbeassumedtobemorereadilyclosed.Second,dataoninfrastructureintensitygapscanbecomparedwithdataongovernanceandthenationalinvestmentclimate.Ifalargegapexists,yettheinvestmentclimateispoor,itcanbeconcludedthatitislesslikelytobeclosed.ResultsForeachoftheindicatorsexamined,thefollowingsectionpresents:
30
• Adefinition;• Anexplanationofitsrelevancetoinvestmentinlong-livedinfrastructure;and• DataontheinvestmentrequiredbyeachcountryinSub-SaharanAfricatocloseits
infrastructureintensitygaprelativetothemostinfrastructure-intensivedevelopingcountry.
NationalindicatorsProducedcapitalintensityProducedcapitalintensitymeasureshowintensivelycapitalisusedinaneconomy.Itisdefinedasthevalueofthetotalstockofproductivecapitalpercapitawhereproductivecapitalcanbephysicalcapitalsuchasmachinery,buildingsandtransportinfrastructureaswellasurbanland.Higherlevelsofproductivecapitalintensityareassociatedwithincreasedlabourproductivity.Ascountriesdevelopandeconomicactivityshiftsawayfromagricultureandtowardsmanufacturingandservices,producedcapitalintensityislikelytoincrease,whichrequiresinvestmentinawiderangeoflonglivedassets.Asthefiguredemonstrates,Nigeriarequiresthemostfutureinvestment,inabsoluteterms,inproductivecapitalbyalargemargin,owingmainlytohighratesofexpectedfuturepopulationgrowth.EthiopiaandtheDemocraticRepublicoftheCongo(DRC),thesecondandthirdhighest,requirelessthanhalfofthisinvestment.ThereisalsoawiderangeofcountriesinthenorthandsoutheastofSub-SaharanAfricarequiringbetween10and20percentofNigeria’sinvestmentneeds.Nigeriarequiresmorethandoubletheadditionalproductivecapitalofanyothercountry
Note: Countriesforwhichdatawasunavailableappearas0.Source: WorldBank(2013,2014),VividEconomics
31
UrbanplanningandinfrastructureCitypopulationgrowthforecastsToensurebasiclivingstandardsaremetforanyincreaseinthepopulationofcities,thequantityofhousingandtheprovisionofamenitiessuchaswater,electricityandsanitationmustbeexpanded.Urbanplanningregulationscanoftenbecomplexandhenceinvestmentplanscantakealongtimetoorganiseandapprove.Moreover,datafromtheUSsuggeststhatsupportinginfrastructuresuchaswaterpipelinesandseweragesystemscanstayinplaceforupto50years(USDepartmentoftheTreasury,2012).WhileassetlivesinSub-SaharanAfricamaybeshorter,urbaninfrastructurecancastashadowonspatialpatternsofdevelopmentthatlastsmuchlongerthanthelifeoftheoriginalasset(e.g.thestreetpatternintheCityofLondonstillbearstheimprintofRomansettlementpatterns).Nationalurbanpopulationgrowthisdefinedasthesumofpopulationchangesinallagglomerationsinagivencountrythatareover300,000peopleinsize,andtheforecastinghorizonisupto2030.Nigeriaexperiencesthevastmajorityofgrowthinthepopulationofcitiesandhencewillrequirethehighestinvestmentinurbanplanningandserviceprovision,asreflectedbelow.TheDRCrequiresaround44percentofthisinvestmentandonlyfiveothercountriesrequiremorethan10percent.CitypopulationgrowthisconcentratedinNigeriaandtheDemocraticRepublicoftheCongo
Note: Countriesforwhichdatawasunavailableappearas0.Source: UNDESA(2014),VividEconomicsShareofurbanpopulationlivinginslums
32
Slumstypicallyhaveahighpopulationdensityandlackaccesstoelectricityandwater.Ascountriesdevelop,theshareoftheurbanpopulationlivinginslumsislikelytodecreaseasincomesriseandpeopleseekbetterlivingconditions.Similartocitypopulationgrowth,thiswillrequiresubstantialinvestmentsinlonglivedinfrastructuretoensurebasicamenitiescanbeprovided.Thefigurepresentstherelativeinvestmentrequiredtoachievethelowestshareofthepopulationlivinginslumsacrossalldevelopingcountries,giveneachcountry’scurrentpopulation.Itdoesnotaccountforfuturegrowthinpopulation.Thisshowsaverysimilarpatterntothatofcitypopulationgrowth,withNigeriaandtheDRCrequiringthemostinvestmentininfrastructurefollowedbyseveralcountriesontheeastcoast.Theshareofurbanpopulationlivinginslumstellsasimilarstorytocitypopulationgrowth
Note: Countriesforwhichdatawasunavailableappearas0.Source: WorldBank(2014b),VividEconomicsIrrigationinfrastructureShareofirrigablelandequippedforirrigationIrrigationcandramaticallyincreasecropyields,theproductivityoflabourandtheincomesofagriculturalworkers.Ascountriesdevelop,farmersarelikelytobecomericher,gainbetteraccesstocreditandbemoreabletoinvestintheinfrastructurerequiredforirrigation,suchasirrigationcanalsandequipmentforsurfaceandpressurisedirrigation.Thustheshareoflandthatisabletobeirrigatedandthatisalreadyequippedwiththenecessaryinfrastructureprovidesanindicationofthecapacityacountryhasforfutureinvestment.Highersharesindicatelowerlevelsofinvestmentaremorelikely.
33
Error!Referencesourcenotfound.indicatesthattheDRChasthelargestpotentialforfutureinvestmentinirrigationinfrastructuremainlyattributabletoitsrelativelylarge(andunequipped)areaofirrigableland,7,000km2.Angola,EthiopiaandMozambiquealsohavelargeunusedpotentialrequiringover40percentofthatoftheDRC.SeveralcountriessuchasCapeVerde,EquatorialGuineaandLesothohavenoinvestmentneedsduetonegligibleareasofirrigableland.TheDRChasthehighestpotentialforfutureinvestmentinirrigationinfrastructure
Note: Countriesforwhichdatawasunavailableappearas0.Source:FoodandAgricultureOrganizationoftheUN(2014),VividEconomicsWaterinfrastructureShareofpopulationwithaccesstoimprovedwaterProvidingaccesstowatertonewcommunitiesrequiresavastnetworkofinfrastructuretoextractwater,throughwaterwellsandreservoirs;treatwater,intreatmentstations;anddistributewater,usingpipelinesandpumpingstations.Asinfrastructureforextractionandtreatmentcanbecostly,thecapacityofreservoirsortreatmentstationsisoftenlargeentailingsignificantinvestments.EvidencefromtheUSsuggestsassetsofthistypehaveausefullifeofapproximately40years(USDepartmentofCommerce,2014).Itcanalsobedifficulttoadjustthelocationofdistributinginfrastructureonceitisbuiltwithoutcausingsignificantdisruptionstodomesticsupply.Thedefinitionof‘accesstoimprovedwater’usedisconsistentwiththatoftheMillenniumDevelopmentGoals.Similarlytotheshareofthepopulationlivinginslums,thefigurepresentstherelativelevelsofinvestmentrequiredtomeetthehighestshareofthepopulationwithaccesstoimprovedwateracrossalldevelopingcountries,giveneachcountry’scurrentpopulation.Itdoesnotaccountforfuturegrowthinpopulation.Nigeria,EthiopiaandtheDRCrequirethehighestlevelsof
34
investmentowingtobothlargepopulationsandlowcurrentlevelsofaccesstowater.Kenya,TanzaniaandUgandaallrequirebetween20to30percentofthatofNigeria.ArangeofcountriesinthenortheastofSub-SaharanAfricahavemid-rangeinvestmentneeds
Note: Countriesforwhichdatawasunavailableappearas0.Source: WorldBank(2014b),VividEconomicsEnergyandcommunicationsElectricitygenerationcapacitypercapitaAscountriesdevelopandincomesrise,bothresidentialandindustrialdemandforelectricityislikelytoincreaseaslargerportionsofthepopulationareconnectedtonationalgrids,consumersdemanddifferentgoodsandmoreadvancedproductionprocessesareputinplace.Toincreasethesupplyofelectricity,investmentisneededingeneration,transmissionanddistributioninfrastructure,forwhichusefulassetlivescanrangefrom30to50years(USDepartmentofCommerce,2014;USDepartmentoftheTreasury,2012).Asindicatedbelow,Nigeriarequiresthehighestlevelofinvestmentinenergygenerationinfrastructureduetoitshighforecastsoffuturepopulationgrowth.Thesetofcountrieswithmid-rangeinvestmentlevelsissimilartothatforwaterinfrastructuresuggestingthatforbothoftheseindicators,populationforecastsplayakeyroleindetermininglikelyinvestment.Electricitygenerationcapacityislikelytoexpandmost,inabsoluteterms,inNigeria,theDRCandEthiopia
35
Note: Countriesforwhichdatawasunavailableappearas0.Source: U.S.EnergyInformationAdministration(EIA)(2014),WorldBank(2014a),VividEconomicsHydropowerproductionrelativetopotentialHydropowerproductionisaparticularlycapital-intensiveformofelectricitygeneration.Moreover,conventionalhydroelectricplantstypicallyhavelargecapacitiesandstayinoperationforlongperiodsoftime.Ifacountry’scurrentlevelofhydropowerproductionisbelowitspotentialproduction,itmaybeassumedmorelikelytoinvestinhydropowerinfrastructureinthefuturetoincreasethis.Potentialproductionisdefinedasthelevelofeconomicallyfeasiblepotentialproduction,thatis,thepotentialforproductionwherethevalueoftheelectricitygeneratedexceedsoperationalcosts.Wheredataforeconomicallyfeasiblepotentialproductionwasnotavailable,anassumptionwasmadeontheproportionoftechnicallyfeasiblepotentialproductionthatiseconomicallyfeasible.Thereareonlyfivecountriesthatshowlikelyfutureinvestmentinhydropowerinfrastructure.Thisisdrivenbytwofactors:lowornegligiblepotentialforhydropowerproductionandthepaucityofdataavailableonsuchpotential.Ethiopiaislikelytoexperiencethemostinvestmentandhasarelativelylargepotentialat268,000GWhperyear.Angolamayhavearound20percentofthislevelofinvestment,whereasMozambique,NigeriaandZambiaconsiderablyless.Veryfewcountriesarelikelytoseesubstantialinvestmentinhydropower
36
Note: Countriesforwhichdatawasunavailableappearas0.Source: TheProgrammeforInfrastructureDevelopmentinAfrica(2010),WorldBank(2014b),WorldEnergyCouncil(2013),VividEconomicsFixedbroadbandinternetsubscriberspercapitaAsurbanisationoccursandruralsettlementsbecomemoredeveloped,demandforcommunicationsinfrastructurewillincrease.Broadbandinternetisanexampleofatechnologythatiswidespreadinthedevelopedworldbuthasachievedlittlepenetrationinthedevelopingworld.Itcanserveasaproxyforthedevelopmentofcommunicationsinfrastructuremoregenerally.Thenumberoffixedbroadbandinternetsubscriberspercapitameasuresthelevelofconsumptionofbroadbandrelativetoacountry’spopulation.Countrieswithalownumberofsubscribersarelikelytoinvestininfrastructuresuchastelecommunicationstowers,withausefulassetlifeof40years(USDepartmentofCommerce,2014),toincreasethis.ThehighestlevelsofinvestmentinbroadbandinternetconnectionswillagainbeseeninNigeria,theDRCandEthiopia.Thoughalargerrangeofcountries,focussedontheeastcoast,seeinvestmentlevelsupwardsof10percentofthatofNigeria.Nigeriaislikelytoinvestmostheavilyinbroadbandandwidercommunicationsinfrastructure
37
Note: Countriesforwhichdatawasunavailableappearas0.Source:WorldBank(2014a,2014b),VividEconomicsTransportPavedroaddensityonarablelandPavedroaddensityonarablelandisdefinedasthetotalkmofpavedroadpersquarekmofarableland.Thisisausefulmeasureofhowwelldevelopedacountry’stransportinfrastructureis;ascountriesdevelop,moresettlementswillbecomeconnectedtothepavedroadnetworkandbuiltupruralsettlementswillbecomemoredenselypopulated.Pavedroadsareusedasopposedtoallroadsastheboththenecessaryinvestmentandassetlifeofnon-pavedroadsislow.Tocomparethislevelofinfrastructureacrosscountries,thelengthofpavedroadisnormalisedbythetotalareaofarablelandasthisexcludeslargeareasofunhospitablelandunsuitableforroadconstruction.InthefigureweseeamoreevendistributionoflikelyinvestmentovercountriesinSub-SaharanAfricanrelativetootherindicators.WhileSudanandtheDRCwillrequirethemostinvestment,Angola,Chad,Ethiopia,Mali,NigerandSouthAfricawillallexperienceapproximatelyhalfthislevel.ItisworthnotingthatseveralcountrieswithaparticularlysmalllandareasuchasCapeVerde,LesothoandtheSeychelleshavebeenexcludedfromthisanalysisandappearas0.InvestmentsinpavedroadsarelikelytobedistributedmoreevenlyacrossSub-SaharanAfrica
38
Note: Countriesforwhichdatawasunavailableappearas0.Source: WorldBank(2014b),VividEconomicsEducationandhealthHospitalbedspercapitaThenumberofhospitalbedspercapitaisausefulindicatorofboththestockoflonglivedinfrastructuretoprovidehealthcareandthequalityofhealthcareasitapproximatesthefloorareaoffunctioninghospitals.Ascountriesdevelop,itmaybethatthepopulationplacesmorescrutinyontheprovisionofpublicservicesandthequalityofhealthcareimprovesasaresult.Thiswillrequiresubstantialinvestmentinhospitalbuildingswhichhaveatypicalusefulassetlifeof36years(USDepartmentofCommerce,2014).Intermsoflikelyinvestmentinhealthinfrastructure,Nigeriarequiresasubstantialamountmoreinvestmentthananyothercountry.ThefigureshowsEthiopia,theDRCandTanzania,thesubsequentthreehighestcountries,arelikelytoinvestonly30percentofthatofNigeria.Again,thisisdrivenlargelybyforecastsoffuturepopulationgrowth.Nigeriawillinvest70percentmoreinhealthinfrastructurethanthenexthighestcountry
39
Note: Countriesforwhichdatawasunavailableappearas0.Source: WorldBank(2014a,2014b),VividEconomicsPublicspendingoneducationasashareofGDPSchoolsaretypicallybuiltsolelyfrompublicfundsandrequireseveralyearstoplanandconstruct.Asaresult,publicspendingoneducationisagoodleadingindicatorofwheninvestmentinschoolbuildingsislikelytooccur.ExaminingthelevelofpublicspendingasashareofGDPprovidesanapproximationofthequalityoftheeducationsystemandhence,isausefulmetrictocomparelevelsofdevelopment.Ascountriesaimtoimprovethequalityoftheireducationsystem,theyarelikelytoincreasepublicspendingoneducationasashareofGDPandinvestininfrastructureforeducation.Asthefigureindicates,whileNigeriaagainhasthehighestlevelsoflikelyinvestmentforeducationalinfrastructure,SouthAfricaisalsolikelytoinvestupto70percentofthatofNigeria.Thisisdrivenlargelybytherelativelyhighlevelofbothcountries’GDP.Angolamayalsoinvestaround40percentwhilemostothercountriesexperiencearelativelysmallinvestment.SouthAfricamayinvestupto70percentofthatofNigeriaineducationalinfrastructure
40
Note: Countriesforwhichdatawasunavailableappearas0.Source: IMF(2014),WorldBank(2014c),VividEconomicsInsuranceandsocialprotectionTotalspendingonsocialandlabourprotectionmeasuresasashareofGDPSocialandlabourprotectionmeasuresoftenrequireseveralyearsofplanningandsubstantialamountsoftechnicalinfrastructuretoimplementandmonitor.Moreover,astheircoverageisoftennationalinsize,theycanbedifficultandcostlytoadjustinthefuture.Moredevelopedcountriesareoftenassociatedwithamoresophisticated,andgenerous,socialsafetynetandsoitislikely,ascountriesdevelop,thattherewillbesignificantinvestmentintheseprotectionmeasures.ThefiguresuggeststhattheexpansionofsocialandlabourprotectionmeasureshasarelativelymutedeffectoncountriesotherthanNigeriaandSouthAfrica.Again,thisislikelytobeduetothedifferencesinthelevelofGDP,asmostcountriesinSub-SaharanAfricawillbestartingfromarelativelylowlevelofGDPandhenceincrementalincreasesintheproportionofGDPspentonprotectionmeasureswillcauserelativelysmallchangesinabsolutespending.SouthAfricaandNigeriawillspendthemostonsocialandlabourprotectionmeasures
41
Note: Countriesforwhichdatawasunavailableappearas0.Source:IMF(2014),WorldBank(2014b),VividEconomicsBarrierstoclosinginfrastructureintensitygapsAsmentionedearlier,itisalsopossibletocalculateinfrastructureintensitygapsrelativetowhatwemightexpectacountry’sinfrastructureintensitytobe,givenitslevelofdevelopmentandothernationalcharacteristics.Thisprovidesanadditionalinsighttotheresultsbycontrollingfortheeffectthatsuchcharacteristicsmighthaveonacountry’sinfrastructureintensity.Thisdoesnotmeanthattheintensitygapwillalwaysbesmallerwhenusingexpectedintensities,as,whileanincreaseinsomecharacteristicswillcauseagiveninfrastructureintensitytorise,otherswillcauseittofall.However,oneoftheparticulareffectsofcontrollingfornationalcharacteristicsinthiswayisto‘cleanout’oftheresultsintrinsiclimitationstoinvestment.Thefigurebelowcontraststheresultsusingbothmethodsfortheshareofthepopulationwithaccesstoimprovedwater.Therelativelevelsofinvestmentrequiredtoclosetheintensitygapfollowasimilarpatternacrosscountries.However,thosecalculatedwithreferencetotheexpectedintensityarealmostalwaysslightlylower.Thisprovidessupportforthemethodusedinthecoreanalysis,suggestingthatthegapsidentifiedforaccesstoimprovedwaterareindeedmorelikelytobeclosed.Theresultsforaccesstowaterarebroadlyconsistentacrossbothbenchmarkmethods
42
Note: Resultsfromeachbenchmarkmethodarestandardisedbythetotalrangeofinfrastructureinvestments.Source: WorldBank(2014d),VividEconomicsEventhisalternativeapproachtobenchmarking,however,mayfailtocaptureallrelevantfactorsaffectingthepropensitytoinvestinnationalinfrastructure.Pooraccesstofinance,anunfavourableinvestmentclimateorineffectivegovernancecanallpreventacountryfromsecuringthenecessaryinvestmenttoclosetheinfrastructureintensitygapsidentifiedinthisanalysis.SomeoftheseindicatorsareincludedintheeconometricanalysisofYepesetal.(2008),yetstatisticalproblemssuchasidentificationandcorrelationofregressorsmaypreventtheireffectsfrombeingproperlyaccountedfor.Tobetterunderstandhowthismightinfluencetheconclusionsdrawnfromthisanalysis,threeindicatorsareexaminedforeachcountry:acompositecreditrating,thelevelofdomesticcreditprovidedbythefinancialsectorandtheaveragescorefromthe2014WorldGovernanceIndex(WGI)update.Thefirsttwooftheseindicatorsrelatetoacountry’saccesstofinancewhereasthelatterrelatestothequalityofgovernance.Thecompositecreditratingisbasedonanassessmentofacountry’sratingwithallthreemajorinstitutions–StandardandPoor’s,Moody’sandFitch–aswellastheperceivedstabilityofthoseratings(TradingEconomics,2014).Thisassessmentisthentranslatedintoascoreoutof100.Therefore,thecompositeratingprovidesanindicationofhoweasyitisforacountrytoraisefinancethroughinternationalcapitalmarkets,aswellasthelikelycostsofborrowing.Bothofthesefactorswillplayaprominentroleinmanycountries’publicinvestmentplans.TheamountofdomesticcreditprovidedbythefinancialsectorasapercentageofGDPprovidesanindicationofhowwelldevelopedthedomesticfinancialsectoris.Similarly,thiswillhave
-
0.2
0.4
0.6
0.8
1.0
Ang
ola
Ben
inB
otsw
ana
Bur
kina
Fas
oB
urun
diC
abo
Ver
deC
entr
al A
fric
an R
epub
licC
had
Com
oros
Con
go, D
em. R
ep.
Con
go, R
ep.
Cot
e d'
Ivoi
reD
jibou
tiE
quat
oria
l Gui
nea
Eri
trea
Eth
iopi
aG
abon
Gam
bia,
The
Gha
naG
uine
aG
uine
a-B
issa
uK
enya
Leso
tho
Libe
ria
Mad
agas
car
Mal
awi
Mal
iM
auri
tani
aM
auri
tius
Moz
ambi
que
Nam
ibia
Nig
erN
iger
iaR
wan
daS
ao T
ome
and
Pri
ncip
eS
eneg
alS
eych
elle
sS
ierr
a Le
one
Som
alia
Sou
th A
fric
aS
outh
Sud
anS
udan
Sw
azila
ndTa
nzan
iaTo
goU
gand
aZa
mbi
aZi
mba
bwe
Sta
ndar
dise
d in
fras
truct
ure
requ
ired
to c
lose
gap
Developing country benchmark Expected intensity benchmark
43
directimpactsonthequantityandcostofcreditavailableintheeconomy,bothtothepublicandprivatesector.ThefigurebelowcomparesstandardisedvaluesofthesetwoindicatorsforcountriesinSub-SaharanAfrica.Thecompositecreditratingisstandardisedbythemaximumpossiblescorewhereasdomesticcreditisstandardisedbythehighestvalueacrossall(developedanddeveloping)countries.MostSub-SaharanAfricancountriesstruggletoscoremorethan40percentoneitherindicator.Someofthecountriesthatwererepeatedlyidentifiedashavingthehighestinvestmentrequirements–NigeriaandtheDRC–havesomeofthelowestscoresonbothindicators,broadly25percentforthecompositecreditratingand15percentfordomesticcredit.Thisissuggestivethatwhiletheremaybealargerequirementforinvestmentifthesecountriesaretomeettheinfrastructureintensitybenchmarkidentified,theymayhavedifficultyindoingso.OneofthehighestscoringcountriesinbothindicatorsisSouthAfricawhichhadhighinvestmentrequirementsforbotheducationalandsocialsafetynetinfrastructure.TakentogetherthissuggeststhatthereislikelytobehighlevelsofthistypeofinvestmentinSouthAfricainthefuture.Thepatternofaccesstofinancedoesnotmatchthatofinvestmentneeds
Note: Themaximumpossiblevaluefordomesticcreditwastakenasthemaximumvalueglobally.Source: TradingEconomics(2014),WorldBank(2014d),VividEconomicsTheWorldGovernanceIndexreportsindicatorsfor215economiescoveringsixkeyareasofgovernance:voiceandaccountability;politicalstabilityandabsenceofviolence;governmenteffectiveness;regulatoryquality;ruleoflaw;andcontrolofcorruption.Thesearebasedon32individualdatasourcesandproducedbyavarietyofsurveys,institutes,thinktanks,NGOs,internationalorganisationsandprivatesectorfirms(WorldBank,2014e).Thisanalysistakesthe
0%
20%
40%
60%
80%
Ang
ola
Ben
inB
otsw
ana
Bur
kina
Fas
oB
urun
diC
abo
Ver
deC
entr
al A
fric
an R
epub
licC
had
Com
oros
Con
go, D
em. R
ep.
Con
go, R
ep.
Cot
e d'
Ivoi
reD
jibou
tiE
quat
oria
l Gui
nea
Eri
trea
Eth
iopi
aG
abon
Gam
bia,
The
Gha
naG
uine
aG
uine
a-B
issa
uK
enya
Leso
tho
Libe
ria
Mad
agas
car
Mal
awi
Mal
iM
auri
tani
aM
auri
tius
Moz
ambi
que
Nam
ibia
Nig
erN
iger
iaR
wan
daS
ao T
ome
and
Pri
ncip
eS
eneg
alS
eych
elle
sS
ierr
a Le
one
Som
alia
Sou
th A
fric
aS
outh
Sud
anS
udan
Sw
azila
ndTa
nzan
iaTo
goU
gand
aZa
mbi
aZi
mba
bwe
Sco
re s
tand
ardi
sed
by p
ossi
ble
max
imum
Composite credit rating Domestic credit provided by banking sector
44
averageofthebestestimateofeachindicatortoprovideacompositeindicatorofgovernancequality.Muchlarge-scaleinfrastructureinvestmentisundertakenbygovernmentandgovernmentinstitutionsmustbeeffectivetosuccessfullyplan,financeandimplementsuchinvestments.Hence,acountry’saverageWGIscoreisagoodindicatorforthelikelihoodthatinfrastructureinvestmentneedswillbemet.Thisaveragescoreisthenstandardisedbythemaximumpossiblescoreacountrycouldachievetogiveapercentagevalue.AsimilarpatterntoaccesstofinanceisseenwiththeaverageWGIscorebelow.Mostcountriesdonotscoreover40percentandthosecountriesthatwererepeatedlyidentifiedashavingthehighestinvestmentrequirementsscoreinthelowerhalf.ThissuggeststhatthedistributionofinvestmentamongSub-SaharanAfricancountriesmay,inreality,bedifferentfromwhattheconclusionsdrawnfromthemainanalysissuggest.TheWGIscoresshowarelativelysimilarrelationshipacrosscountriesasaccesstofinance
Source: WorldBank(2014e),VividEconomicsConclusionsandnextstepsInitialconclusionsLookingacrosstheindicatorsofinfrastructureintensityasawhole,NigeriaappearstohavethehighestabsoluteinvestmentneedsinSub-SaharanAfrica–indeed,ithasthehighestneedsfornineofthetwelveindicatorsexaminedoftenbyasignificantmargin.EthiopiaandtheDRCalsoscorehighlyonawiderangeofindicatorspointingtoarelativelyhighoveralllevelofinvestmentneeds.Inallthreecases,thekeydriverofthisisthelargesizeofthecountrybothintermsofpopulationandlandarea.Aseachinfrastructureintensitygapismultipliedbytheabsolutevalueofthevariableunderlyingtheintensitytoarriveatanabsolutelevelofinvestment,evenifother
0%
20%
40%
60%
80%
Ang
ola
Ben
inB
otsw
ana
Bur
kina
Fas
oB
urun
diC
abo
Ver
deC
entr
al A
fric
an R
epub
licC
had
Com
oros
Con
go, D
em. R
ep.
Con
go, R
ep.
Cot
e d'
Ivoi
reD
jibou
tiE
quat
oria
l Gui
nea
Eri
trea
Eth
iopi
aG
abon
Gam
bia,
The
Gha
naG
uine
aG
uine
a-B
issa
uK
enya
Leso
tho
Libe
ria
Mad
agas
car
Mal
awi
Mal
iM
auri
tani
aM
auri
tius
Moz
ambi
que
Nam
ibia
Nig
erN
iger
iaR
wan
daS
ao T
ome
and
Pri
ncip
eS
eneg
alS
eych
elle
sS
ierr
a Le
one
Som
alia
Sou
th A
fric
aS
outh
Sud
anS
udan
Sw
azila
ndTa
nzan
iaTo
goU
gand
aZa
mbi
aZi
mba
bwe
Sco
re s
tand
ardi
sed
by p
ossi
ble
max
imum
Average WGI score
45
countrieshavealargergap,themuchlargerunderlyingvariablesseeninthesethreecountriesleadtoalargerlevelofinvestmentneed.Thiseffectbecomesmorepronouncedwhenconsideringforecastsofthesevariablessuchascitypopulationgrowth.However,thesesamecountriestypicallyperformpoorlywhenlookingattheenablingenvironmentforinfrastructureinvestment.CompositecreditratingsareroughlyaroundthemidpointofSub-SaharanAfricaindicatingeachcountryhaspooraccesstofinancefrominternationalsourceswhilethelevelofdomesticcreditavailableiswithinthelowestquartilesuggestingresourcesavailabledomesticallyareevenscarcer.ThesecountriesalsohaveanaverageWGIscorebetween20and30percentwhichmaymeanthatevenwithfavourableinvestmentconditions,publicinstitutionsmayfailtoorganiseandimplementsuchinvestments.Overall,itseemsthatNigeria,EthiopiaandtheDRCarelikelytoexperiencesomeinvestmentinlong-livedinfrastructureinthemediumterm,particularlyconcerningurbanplanning,housingandamenitieshowever,thereareunlikelytobetheleadersofSub-SaharanAfricathatthemainanalysissuggests.Twoparticularintensityindicatorsthatprovidedadifferentperspectiveweretheshareofirrigablelandequippedforirrigationandhydropowerproductionrelativetopotential.Withinboth,onlyasmallsubsetofcountrieswerelikelytoexperienceanysignificantinvestmentinthefuture.WhiletheDRCstillhadthehighestinvestmentneedsforirrigationandEthiopiaforhydropower,othercountriessuchasAngola,MozambiqueandZambiaalsorequiredasubstantialamountoftheleaders’needs.Thesethreecountriesscoredmoderatelyonboththeinvestmentclimateindicatorsandthequalityofgovernanceindicatorsuggestingthatmoderatelevelsofinvestmentininfrastructureinthesesectorsislikely.SouthAfricahadrelativelyhighinvestmentneedsforbotheducationalandsocialprotectioninfrastructure.SimilartotheeffectsofNigeria’slargepopulation,thiswascausedprimarilybySouthAfrica’srelativelyhighGDPwhichcausedevenamodestintensitygaptotranslatetosubstantialabsoluteinvestmentneeds.SouthAfricaalsoscoredrelativelyhighlyinboththeaccesstofinanceindicatorsandtheaverageWGIscoresuggestingthatiftherewassufficientdemand,theopportunityforinvestmentsisavailable.Overall,thisindicatesthatsignificantinvestmentislikelytooccurininfrastructuretoprovidebotheducationandsocialandlabourprotectioninthefuture.NextstepsThisreportpresentshaspresentedasummaryofthemethodologyusedfortheanalysis,theinitialfindingsandconclusionshowever,theanalysisisongoing.Specificaspectsoftheassessmentmethodologyandhence,theconclusionsdrawnwillcontinuetoberefined.Forthenextdraft,weproposetoundertakethefollowingchanges.Foreachintensityindicator,wewillrefinethesetofcomparisoncountriestoexcludeoutlierswhichmayexaggeratetheinvestmentneedsofSub-SaharanAfricancountries.Thiswillbedonebyexaminingarelatedvariableandtruncatingthedatasetbyasensiblevalue,forexample,inthecaseofpavedroaddensity,anycountrywithatotallandareaoflessthan1,000km2wasexcluded.Toensurewearelookingatthemostrelevanttimeframefortheproject,wewillrestrictforecastsoftheunderlyingabsolutevariablessuchaspopulationandGDPto10yearsinthe
46
future.Thiswillalsohelptoensurethereisconsistencyacrosstheintensityindicatorsexamined.Theinvestmentneedstomaintaintheshareofpopulationlivinginslumsandwithaccesstowateratthebenchmarklevelinthefuturewillalsobeadded.Thiswasnotincludedinthisdraftduetotimeconstraints.Toensurethattheanalysisdoesnotresttooheavilyontheinfrastructuregapframework,twonewabsoluteindicatorswillbeadded–plannedadditionstohydropowercapacityandtheareaoflandpredictedtochangefromruraltourban.Thiswillhelptoaddresstheweaknessesinthegapanalysis,namelythatgapsmaypersistasitisdifficulttosecuresufficientinvesttoclosethem.Withineachofthechloroplethmaps,wewilldistinguishbetweenthosecountriesthatappearas0becausetheyrequirenoinvestmentandthosethatappearas0becausethereisnodataavailable.Foreachofthechloroplethmaps,thekeywillbeenlargedsoitismorereadableandtheheadingincludingthecodenamewillberemoved.
47
TASK 2: PRACTICAL EXAMPLES OF LONG-TERM DECISIONS
Theaimofthistaskistoidentifyanypracticalexamplesinthegreyorpeer-reviewedliteratureofwheretheeconomicanalysisoflong-termdecisionmakinghasbeenparticularlygood,preferablyinareasdirectlyrelevanttoadaptationinAfricaorfailingthisinotherrelevantareas.Thestartingpointforthistaskhasbeentocompilethestudyteam’sexistinginventoriesofadaptationeconomicstudiesinAfrica,andmoregenerally,economicanalysisoflong-termdecisionmakingforadaptation.
Studies on the Economics of Adaptation in Africa Previousreviewsofthecostsandbenefitsofadaptation(OECD,2008;UNFCCC,2009;Agrawalaetal,2011;Chambweraetal.,2014)generallyreportthattheevidencebaseonthecostsandbenefitsislow.However,overrecentyears,additionalevidencehasemerged.Thisisduetoalargenumberofglobalandcountrylevelinitiativesontheeconomicsofadaptation,andalsosectoralstudiesthatapplyexistingoptionstonewcontextsorlocations.Arecentreviewandcompilationofthesestudies(ECONADAPTproject,2015)hasidentifiedseveralhundredstudies.Overrecentyears,anumberofinitiativeshaveemergedthatprovideestimatesoftheearlycostsofadaptationinAfrica.Thecoverageisshownbelow.
Nationalandsub-nationalleveladaptationcoststudiesinAfrica
Nationalassessmentsorinitiatives Otherstudieswithnationalorsub-nationalcoverage
Source:ECONADAPT,2015.Fourkeyinitiativeshavebeenundertaken:theWorldBankEACCcountrystudies(WorldBank2010),UNDPAssessmentofInvestmentandFinancialFlows(IFF)toAddressClimateChange(UNDP,2011),theUNFCCCNationalEconomic,EnvironmentandDevelopmentStudy(NEEDS)(UNFCCC,2010)andtheRegionalEconomicsofClimateChangeStudies(RECCS).Thesestudies
48
usedifferentmethods,andhavedifferentassumptions,makingdirectcomparisondifficult.Nonethelesstheyprovidesomeusefulinformationforthecurrentstudy.TheWorldBankEconomicofAdaptationtoClimateChange(WorldBank,2010)studyusedglobalscenario-basedimpact-assessmenttoestimatetheeconomiccostsofclimatechange,thenestimatedthecostsofadaptationtoachievepre-climatelevelsofwelfare.Thestudyconsideredtwoclimaticfutures,withminimumandmaximumtemperatureand‘wetter’and‘drier’rainfalloutcomes,findingthathighercostsarosewithwetterscenariosduetoimpactsoninfrastructure.Thechoiceofaggregationrulealsoaffectedtheestimates,notablywhethergainsfromclimatechangewereaddedtoadaptationcosts.Thestudyincludedanexplicitconsiderationoffuturedevelopmentbaselines,aswellastheeffectsofclimatechangebysector,anddidconsider(climate)uncertainty.However,asthereportacknowledges,adaptationcostswerestillcalculatedasthoughdecision-makersknowthefuturewithcertainty,withestimatescalculatedforeachdiscreteprojectioninturn:inrealitycostswouldbehigherduetotheneedtohedgeagainstarangeofoutcomes.Furthermore,thecoverageofimpactsandsectorsispartial(andsimilartotheUNFCCCstudy)focusingonasmallnumberofimpacts(albeitimportantones),i.e.wherequantificationwaspossible.TheglobalstudyreportedthatthecostsofadaptationforSubSaharanAfrica–fortheperiod2010to2050(thusfora2°Cwarmerworld)–wereUSD14billiontoUSD17billionperyear(2005$billions,nodiscounting).ThiscomparedtoglobalcostsindevelopingcountriesofUSD71billiontoUSD98billion(aboutthesameorderofmagnitudeascurrentforeignaid).ThisvaluewascitedintheIPCC5thAssessmentReport,thoughthisacknowledgedtheshort-comingswiththevalue.Theglobalstudywascomplementedwithanumberofcountrystudies–ofwhichthreewereinAfrica(Ethiopia,GhanaandMozambique).Thesealsousedsectorimpactassessmentthoughalsoincludedwidereconomicmodelling.ThestudiesusedtheDIVAmodelforsea-levelrise,agriculturalcropmodels,watermanagementmodels,andsomeinfrastructuredamagefunctions.Thesecountrystudiesindicatehighercoststhantheglobalstudy,around20%higherduetotheconsiderationofcross-sectoralandsociallycontingenteffects.However,insomecases,thecountrystudiesindicatedverymuchhighercoststhantheglobalanalysis.Forexample,thecountrystudyinEthiopia(WorldBank,2010)estimatedthecostsofadaptationandtheresidualimpactsforthisonecountryalonecouldbe$1.2billionto$5.8billionperyear(2010–2050).Similarly,thecostsforMozambiqueforaddressingsealevelrise(WorldBank,2010c)wereestimatedat$0.3to$0.8billionperyearbythe2030s.AnalternativesetofcountryanalysiswasproducedundertheUNDPInvestmentandFinancialFlowstoAddressClimateChangeinitiative,whichusedadifferentmethod,centredoninvestmentandfinancialflows,i.e.estimatingadaptationmark-upsonfutureinvestmentprofiles.Thesestudiesestimatetheadditionaladaptationcostsrequiredthroughto2030.Atotalof15countrystudieswereundertaken,withAfricanstudiesinGambia,Liberia,Namibia,Niger,Togo,eachfocusingon1or2keysectorseach(primarilyagricultureand/orwater).Again,thesecostsindicatehighercoststhanimpliedbytheglobalassessments.Thiscanbeexplainedpartlybythedifferentmethods,assumptionsandcoverage.TheIFFstudiesarebettergroundedincurrentpolicyandtheyincludeamuchgreatercoverageofrisksastheylooktobuildresilienceacrossallexistingpolicyareas.Theyalsohaveamorerealisticassessmentofcostsofdeliveringadaptation(includingimplementationandpolicycosts,andthecoststothe
49
privateaswellasthepublicsector)andtheydonotaggregatewinnersandlosers.However,theyincludesomecostsforactionthataretargetedatreducingtheexistingadaptationdeficit,theyoftenareoftenfocusedonirrigationoptions,andtheyomitthebenefitsoftradeinoffsettingtheneedfordomesticaction.SummaryoftheUNDPIFFassessments–totaladditionalinvestmentcosts(USDto2030)
Country I&FFassessments
andresults
Estimatedcosts
Gambia Agriculture–andwateradaptation
US$435million[$1440undiscounted]isneededtoadapttotheeffectsofclimatechangeintheagriculturesector,andUS$17millionisneededtoadapttotheeffectsofclimatechangeinthewatersector.
Liberia Agriculture-adaptation
Fortheagriculture/livestocksector(adaptationtotheimpactsofclimatechange)US$1.41billionisneededtoadapttotheeffectsofclimatechange.
Namibia Land-usechange-adaptation
Fortheland-usesector(adaptationtotheimpactsofclimatechange),theoverallincrementalcostsofthemeasuresareUS$3.0billion(livestockandcrops)[discounted].
Niger Agriculture/livestock-adaptation
Fortheagriculture/livestocksector(adaptationtotheimpactsofclimatechange)US$374millionisneededtoadapttotheeffectsofclimatechangeintheagriculture/livestocksector.
Togo Agriculture-adaptation
TheI&FFassessmentontheagriculturesectorfocusedoncrops,livestockandfisheries.US$167millionareneededtoprotectagricultureagainsttheimpactsofclimatechange.
Source:UNDP(2010)Afurtherstudy–theUNFCCCNEEDSprojectwasundertakeninanumberofcountriesincludingEgypt,Ghana,MaliandNigeria(UNFCCC,2010).Thisassessedtheshort-andlong-termcostsofadaptationfinancingneeds.Thesestudiesalsoindicatehighindividualcountryestimates,thoughthecountriesuseddifferentmethodologiesandapproaches,overdifferenttime-scales.Aggregatedestimatedshort-andlong-termfinancialcostsofadaptationasreportedby
countriesparticipatingintheNationalEconomic,EnvironmentandDevelopmentStudyfor
climatechangeproject
Country Short-term
costs(2020)
Long-term
costs(2050)
Comments
Egypt 2.8billion 4billion Costestimatescoverobservationsystems,agriculture,irrigation,coastalzones,socioeconomicstudiesofthecostofadaptation,andcapacity-buildingandtraining.
Ghana 697.2million 701.7million Estimatesofthecostofcontainingtheeffectsofclimatechangeonhealth,agricultureandcoastalzones
Nigeria 11.45billion(annually)
20.69billion(annually)
Estimatedincrementalcostsofadaptationmeasuresinrelationtowater,agriculture,healthandtransportation
SourceUNFCCC,2010.Alongsidethis,alargeanumberofotherregionalandcountrylevelinitiativeshavebeenundertaken,includingtheRECCstudiesinKenyaandRwanda(SEI,2009)andTanzania(GCAP,2010),andalsostudiesinEthiopia(Watkissetal,2013;FDRE,2015),Tanzania(GoT,2014)andUganda(CDKN,forthcoming).
50
Otherstudiesinclude:
• ApplicationoftheDIVAmodeltoallAfricancountries,withdisaggregatedcostsofsealevelriseandadaptationcosts(Brownetal,2009).Considerationoftherisksandadaptationcostsfor136globalcoastalcities(ofwhichAbidjan,Alexandria,AlgiersandBanghaziinAfricawereidentifiedaspriorities)(Hallegatteetal,2013).Atamorelocalisedlevel,thereisthestudyofadaptationincoastalzonesinDurban,SouthAfrica(Cartwrightetal,2013).
• Someestimatesofthecostsofadaptingexistingbuildingnewclimate-proofedurbanwaterinfrastructurein(sub-Saharan)Africa(Muller,2007)estimatedatUS$2-5billionannual.AfDB(2011)andDocziandRoss(2014)reviewotherestimatesforAfricainthisarea.ThereisalsothestudyofwaterinfrastructureinvestmentintheBergRiver,SouthAfrica(AIACC,2006),andwaterresourcemanagementinKenya(SEI,2009)aswellasEthiopia(WorldBank,2010)andinthewatersectorinMorocco(Mohamed,2013).
• Foragriculture,theapplicationtoagriculturaladaptationinGambia(AIACC,2006),adaptationcost-benefitcurvesinMali,Moptionclimateshifts(ECA,2009),benefitcostanalysisforagricultureinMalawi(Brancaetal,2012)andagriculturalCBAinUganda(IIED,2012),aswellaneconomicanalysisofadaptation(usingstakeholderCBA)intheLakeChilwaCatchmentinMalawi(Lundukaetal,2013)andonclimatesmartagriculture(McCarthyetal.,2011),aswellasseveralRicardianstudies(Kurukulasuriyaetal.,2007;2008;2011)andtheEACCcropsmodelsandIFFassessments.ThereisalsotheTanzaniaagriculturalsectoradaptationplan(GovernmentofTanzania,2014
• Adaptationcoststudiesonroadinfrastructureindevelopingcountries,includinginEthiopiaandGhana(WorldBank,2010).
• AnalysisofhealthadaptationinTanzaniaforwaterrelateddisease(ECA,2009)andKenyaformalaria(SEI,2009).
Mostoftheseestimatesarefromthegreyliterature.Moreover,mostoftheevidenceisbasedonclassicscenario-basedimpactassessmentmethods.Thismeansthemajorityofthestudiesaretheoretical,focusontechnicaladaptation,andignoreuncertainty.TheseearlierstudiesshowadaptationhasveryhighBCRsandpotentiallylowcosts,thoughmorerecentstudiesindicatetheyareprobablyover-optimistic.Intermsofadaptationdecisionmakingunderuncertainty,thereareonlyalimitednumberofstudiesfoundforAfrica,discussedinthenextsection.
Studies on Long-term Adaptation Decision Making Thisisagrowingevidencebaseandexamplesontheuseofdecisionsupportapproachesforadaptationappraisal,thoughasshownabove,thenumberofsuchstudiesinAfricaissmall.Thesetoolsareakeycomponentoftheconsiderationofadaptationinmediumtolong-termclimatedecisions.Theyincludeconventionaldecisionsupportmethods,notablycost-benefitanalysis,cost-effectivenessanalysisandmulti-criteriaanalysis.Italsoincludesasetofapproachesthatallowforconsiderationofuncertainty,notablyrealoptionsanalysis,robustdecisionmaking,portfolioanalysisanditerativeriskmanagement.Adetaileddescriptionandreviewofthesemethodsandtheirapplicationtoadaptation,hasbeenundertakenaspartoftheMEDIATIONandIMPACT2Cprojects(seealsoWatkissetal,2014:Rangeretal,2010:Frontier,2013).Theyaresummarisedbelow.
51
DecisionSupportToolsforAdaptationSource:ECONADAPT,2015,updatingWatkissetal.,2014.Whilstthesetoolshaveprimarilybeendevelopedinthecontextofproject-levelappraisal,inprincipletheycanbeusedtoprioritisepolicyinitiativesatthenationalandsectoralscale(thoughprincipallyasanorganisingframework,withsemi-quantitativeversionsduetodataavailability).Attheprojectlevel,wheredataisavailable,theycanbeappliedmorequantitatively.Examplesaregivenbelow.
52
ExamplesofAppraisalMethodsintheAdaptationContext
Tool PublishedExampleApplications
Cost-Benefit
Analysis
AIACC(2006).ThisSouthAfricanstudyexaminedthebenefitsandcostsofavoidingclimatechangedamagesthroughstructuralandinstitutionaloptionsforincreasingwatersupplyintheBergRiverBasinintheWesternCapeProvince.TheUBA(2012)projectappliedcost-benefitanalysistoconsider28adaptationoptionsforGermany.
Cost-
Effectiveness
Analysis
Boydetal(2006)undertookadetailedapplicationofcost-effectivenessforwaterresourcezonesandtheadaptationresponsetoaddresshouseholdwaterdeficitsintheUK.Tainioetal.(2013)investigatedthecost-effectivenessofadaptationoptionsthatcouldmaintainthebiodiversityofFinnishsemi-naturalgrasslandsunderachangingclimate.
Multi-
criteria
analysis
VanIerlandetal.(2007)(DeBruinetal.(2009)appliedMCAtoassessadaptationoptionsfortheNetherlandsaspartoftheRouteplannernationalstudy.ThisusedaqualitativeMCA,whichincludedvariousadaptationcriteria.AquantitativeMCAwasusedintheThamesEstuary2100project(EA,2009:2011)aspartofabroaderstudylookingatfuturecoastalflooddefencesforLondon.TheMCAwasusedtoincludequalitativecriteria(environment,heritage,etc.)alongsideformaleconomiccost-benefitanalysis.
RealOptions
Analysis
JeulandandWhittington(2013)appliedrealoptionanalysisforawaterresourceplanningcasestudy(largewaterstorageprojects)inEthiopiaalongtheBlueNile.VanderPol,etal(2013)lookedatoptimaldikeinvestmentsunderuncertaintywithlearningaboutincreasingwaterlevels.LinquitiandVonortas(2012)analysedcoastalprotectioninvestmentsandfoundusingrealoptionsledtobetteruseofresourcesinDhakaandDar-es-Salaam.Scandizzo(2011)appliedROAtoassessthevalueofhardinfrastructure,restorationofmangrovesandcoastalzonemanagementoptionsinMexico.Kontogiannietal(2013)usedROAtoassessthevalueofmaintainingflexibility(e.g.scalingupordown,deferral,accelerationorabandonment)toengineeredstructuresinGreece.Gersoniusetal,2013appliedtowaterandfloodriskinfrastructureinanurbansiteintheUK,Dobes,2010appliedtohousingdesignforfloodinginMekongDeltaVietnamandWorldBank2009appliedtoagriculturalirrigationinMexico.
Robust
Decision
Making
Acomprehensive,formalapplicationofRDMwasundertakenbyLempertandGroves(2010)forSouthernCalifornia’sRiversideCountyInlandEmpireUtilitiesAgency(IEUA).ThereisanapplicationofrobustdecisionmakingforplanningcoastalresilienceforLouisiana(GrovesandSharon,2013),anapplicationtowaterscarcityintheColoradoRiverBasin(Grovesetal,2013)andtofloodriskmanagementinHoChiMinhCityinVietnam(Lempertetal,2013).DessaiandHulme(2007)presentanexampleoftheapplicationforRDMtolookatclimateuncertaintyforwatersupplymanagementintheUK.Nassopoulosetal(2013)appliedtodamdimensioningforasmallcatchmentinGreece.DyszynskiandTakama(2010)appliedRDMtomicro-insuranceinEthiopia.
Portfolio
Analysis
CroweandParker(2008)provideanapplicationoftheapproachforforests,toinvestigategeneticmaterialthatcouldbeusedfortherestorationorregenerationofforestsunderclimatechange.Hunt(2009)appliedportfolioanalysistoacaseoffloodmanagementatthelocalgeographicalscale,forriverfloodrisksintheUK,lookingatportfoliosofhardandsoftoptions
IterativeRisk
Assessment
TheThamesEstuary2100project(EA,2009:2011:ReederandRanger,2011)developedatidalflood-riskmanagementadaptationplanforLondonusinganiterativeplanningapproachandadaptationpathways,withadetailedmonitoringandevaluationstrategy.IntheNetherlandstheDeltaprogrammehasincludedconsiderationofriverflooding(DeltaProgramme,2008:2011:2014)movedtodynamicadaptationpathways.AniterativeapproachforportdevelopmentcomparingupgradeableversusoneoffinvestmentswasundertakenbytheIFC(2011)ontheportofCartagena,Colombia.Watkissetal(2013)appliedaniterativeapproachtothedevelopmentoftheClimateResilienceStrategyforAgricultureinEthiopia.Darchetal.(2011)assessedtheeffectsoflongtermclimateuncertaintyonwaterinvestmentplanninginLondonandlooktoidentifyrobustoptionsforsupplyanddemandanddevelopdecisionpathways
Source:ECONADAPT,2015.
53
Arecentreview(ECONADAPT,2015)hasfoundthatthenumberofeconomicapplicationsofthenewtoolsremainslow,thoughthereareexamplesinseveralsectors.
Economicapplicationofnewdecisionsupporttoolsforadaptation.
Source:ECONADAPT,2015.AsmallnumberofthenewdecisionsupporttoolshavebeenappliedinAfrica.
• ThereisastudythatusesrealoptionsanalysisfortheBlueNileinEthiopia(JeulandandWhittington,2013)forwaterinvestmenttoidentifyflexibilityindesignandoperatingdecisionsforaseriesoflargedams.Theirresultsdonotidentifyasingle‘best’investmentplan,buthighlightconfigurationsrobusttopooroutcomesbutflexibleenoughtocaptureupsidebenefitsoffavourablefutureclimates.
• LinquitiandVonortas(2012)analysedcoastalprotectioninvestmentsandfoundusingrealoptionsledtobetteruseofresourcesinDhakaandDar-es-Salaam.
• DyszynskiandTakama(2010)appliedRDMtomicro-insuranceinEthiopia.
• ThereisEthiopianClimateResilienceStrategy(Watkissetal.,2013;FRDE,2014)whichusedaniterativemanagementapproach.Theapproachhighlightedthatunderconditionsofhighfuturechange(e.g.highwarmingscenariosorearlynegativeimpactsoncrops),costspost2020wouldrisemorequickly,asportfoliooptionswouldneedtobebroughtonstreamquicker.Importantly,theanalysisidentifiedsomeareasoflong-termriskthatwarrantedearlyaction(i.e.now),notablyforcoffee,duetothelongercropcyclesandthelongtime-scaleforchangesincultivarorareas.
• Thereisastudythatconsiders(andcosts)agriculturaloptionsusingiterativeadaptivemanagementplanninginMalawi(Matiyaetal.,2011).
Ananalysisofthesebroaderlistofstudiesrevealthatmosteconomicapplicationsarehypotheticalstudies,oftenfocusedontechnicaladaptation,withlessapplicationsindirectprojectorpolicyappraisals(e.g.forrealschemesorsectors).ThemoreappliedstudiesincludetheapplicationofiterativeriskmanagementinnationalpolicyappraisalintheNetherlands(iterativemanagementfortheDeltaProgramme,2014)andEthiopia(intheNationalClimateResilienceStrategy:FDRE,2014),andalsoattheprojectlevelwiththeapplicationtotheLondonThamesEstuary2100project(EA2009:2011).Italsoincludesapplicationsofrobust-decisionmakingtowatermanagementintheColoradoriver(Grovesetal,2013),floodriskmanagement
54
inHoChiMinhCityinVietnam(Lempertetal,2013)andplanningcoastalresilienceforLouisiana(GrovesandSharon,2013).Whilereal-optionsanalysishasbeenappliedinpracticeinthemitigationdomain,theapplicationtoadaptationremainstheoretical,asisportfoliotheory:ROAhasalsofocusedonsealevelrise,whichiseasiertoassessduetoitsslow-onsetnature,andknowndirectionofchange.Therehasalsobeenworkonthepotentialapplicabilityoftheseapproaches,aspartofdecisionsupport.Rangeretal.(2010)presentedaframeworkfordecisionmaking.
Selectionofquantitativemethodsfordecision-makingunderuncertainty
Source:Rangeretal.,2010.AsimilarframeworkwasadvancedbyFrontierEconomics(2013).
55
Frameworkforgatheringdataandselectingappraisalmethodology
Source:FrontierEconomics,2013.Amorerecentanalysis(Watkissetal.,2014:ECONADAPT,2015)consideredtheapplicability.Thisfoundthattheseapplicationsshowtherearenohard-or-fastrulesonwhichtooltousewhen.Itisclear,however,thatcertaintoolslendthemselvesmoretospecificcontextsorsectors.Thetypeofadaptationproblem(andobjective)willthereforeshapethechoice.Importantly,noneofthesetoolsisuniversallyapplicabletoalladaptationproblemsandtheyeachhaveparticularstrengthsforcertaintypesofdecisionsand/orapplications.Policy-levelassessmentsaremorelikelytomakeuseoftheestablishedtoolsthatprovideaframeworkformoreaggregatedanalysis,althoughiterativeriskframeworksandrobustdecisionmakingalsohavehighpotentialforprogramme/sectoranalysis(thoughtheyaremoreprovenattheprojectlevel).Attheprojectscale,toolselectionwillbeinfluencedbydataavailabilityandthelevelofuncertainty.Severalofmoreeconomicfocusedapproaches(realoptionsandportfoliotheory)requireprobabilisticinputs,whichischallengingforfutureclimateprojections,andtheyalsorequirequantitativeinputs.Theapplicationoradaptationproblemalsodeterminesthesuitabilityofthedecisiontool.Forexample,foranalysisthatisfocusedoncurrentclimatevariability(theadaptationdeficit),existingdecisionsupporttoolscanbeused,includingCBA.Fortheanalysisofshort-termdecisionswithlonglife-timesandlonger-termchallenges,agreaterfocusonnewdecisionsupporttoolsiswarranted.RDMhasbroadapplicationforcurrentandfuturetimeperiods.Wheninvestmentsarenearerterm(especiallyhighupfrontcapitalirreversibleinvestments),andwherethereisanexistingadaptationdeficit,ROAisapotentiallyusefultool,whereasforlong-termapplicationsinconditionsofalowcurrentadaptationdeficit,IRMmaybemoreapplicable.Importantlywhilethetoolsarepresentedindividually,theyarenotmutuallyexclusive.
56
AttributesandApplicationofDecisionSupportMethodsforAdaptation
Decision-
SupportToolStrengths Challenges Applicability Potentialuse
Cost-Benefit
Analysis
Wellknownandwidelyapplied.
Valuationofnon-marketsectors/non-technicaloptions.Uncertaintylimitedtoprobabilisticrisks/sensitivitytesting.
Mostusefulwhenclimateriskprobabilitiesknownandsensitivitysmall.
Toidentifylowandnoregretoptions(short-term)inmarketsectors.AsadecisionsupporttoolwithinICRM
Cost-
Effectiveness
Analysis
Analysisofbenefitsinnon-monetaryterms.
Singleheadlinemetricdifficulttoidentifyandlesssuitableforcomplexorcross-sectoralrisks.Lowconsiderationofuncertainty
Asabove,butfornon-monetarysectors(e.g.ecosystems)andwheresocialobjective(e.g.acceptablerisksofflooding).
Asabove,butformarketandnon-marketsectors.
Multi-
Criteria
Analysis
Analysisofcostsandbenefitsinnon-monetaryterms.
Reliesonexpertjudgementorstakeholders,andisoftensubjective,includinganalysisofuncertainty.
Wheremixofquantitativeandqualitativedata.Canincludeuncertaintyperformanceasacriteria
Asabove,butalsouseforscopingoptions(policylevel).Cancomplementothertoolsandcapturequalitativeaspects.
IterativeRisk
Assessment
Frameworks
Iterativeanalysis,monitoring,evaluationandlearning.
Challengingwhenmultiplerisksactingtogetherandthresholdsarenotalwayseasytoidentify.
Usefulwherelong-termanduncertainchallenges,especiallywhenclearriskthresholds.
Forappraisalovermedium-long-term.Alsoapplicableasaframeworkatpolicylevel.
RealOptions
Analysis
Valueofflexibility,information.
Requireseconomicvaluation(seeCBA),probabilitiesandcleardecisionpoints..
Largeirreversibledecisions,whereinformationonclimateriskprobabilities.
Economicanalysisofmajorcapitalinvestmentdecisions.Analysisofflexibilitywithinmajorprojects.
Robust
Decision
Making
Robustnessratherthanoptimisation.
Highcomputationalanalysis(formal)andlargenumberofruns.
Whenlargeuncertainty.Canuseamixofquantitativeandqualitativeinformation.
Identifyinglowandnoregretoptionsandrobustdecisionsforinvestmentswithlonglife-times.
Portfolio
Analysis
Analysisofportfoliosratherthanindividualoptions
Requireseconomicdataandprobabilities.Issuesofinter-dependence.
Whennumberofcomplementaryadaptationactionsandgoodinformation.
Projectbasedanalysisoffuturecombinations.Designingportfoliomixesaspartofiterativepathways.
Source:ECONADAPT,2015.Itisworthnotingthatthedifferencesbetweenthetoolsarenotlimitedtodataandcapacityconstraintsbutmayhaveamaterialimpactontheorderofprioritisationofadaptationoptions.Klijnet.al.(2014)demonstratesthatapplyingRDMresultsinadifferentorderfromCBA,andCBAproducesadifferentorderfromCEA.However,akeyfindingisthatallthenewmethodsareresourceintensiveandtechnicallycomplex.Indeed,thisconstrainstheirformalapplicationtolargeinvestmentdecisionsormajorrisks,i.e.priorityprojectsforadaptationorspecificadaptationprojects,ratherthanmainstreaming.Theseissuesarelikelytolimitfutureapplicationinthemainstreamingcontext.Theseissuesarelikelytolimitfutureapplicationinthemainstreamingcontext,especiallyinAfrica(thoughexperiencehasalsofoundthisisdifficultintheUK,asshownbyearly
57
implementationexperienceofrealoptionsanalysisguidance(HMT,2008;Mullan,personalcommunication).Todatetheyhavebeenusedtosupportnon-mainstreamedadaptationactivities/projects,butthetranslationintosectoralcontexts,withanalystswho–forexample-maynothaveextensiveknowledgeofclimateprojectionsanduncertaintyislikelytobedifficult.Acriticalquestionisthereforewhethertheconceptsinthesedetailedtoolscanbeusedin‘light-touch’approachesthatcapturetheirconceptualaspects,whilemaintainingadegreeofeconomicrigour,bothatpolicyandprojectlevel.Thiswouldallowawiderapplicationinqualitativeorsemi-quantitativeanalysis.ThiscouldincludethebroaduseofdecisiontreestructuresfromROA,theconceptsofrobustnesstestingfromRDM,theshifttowardsportfoliosofoptionsfromPA,andthefocusonevaluationandlearningfromIRMforlong-termstrategies.Therehasbeensomeearlyprogressadvancingthesetypesoflight-touchapplications,e.g.Hallegatteetal.(2012);Rangeretal(2013).However,asyet,thereisnothingthatseemssuitableinbalancingthetrade-offbetweenquantitativeanalysisandpragmaticapplicationandthisremainsapriorityfordevelopment.
Discussion WhilethereisagrowingliteratureontheeconomicsofadaptationinAfrica,muchoftheavailableevidenceisnotsorelevantforthisstudy,eitherbecauseitfocusesonaddressingearlyadaptationdeficits,oritappliesascience-firstimpact-assessmentframework.Thereare,however,awidesetofstudiesthatdemonstratetheconsiderationofuncertaintyinadaptationdecisionsupportwhicharerelevant,andthesedoincludesomeexamplesforAfrica.However,thesearecomplextoapply,andrequirecapacity,timeandresource,whichislikelytolimittheirapplication.Afocusforthestudyisthereforetoinvestigate‘light-touch’approachesthatcapturetheirconceptualaspects,whilemaintainingadegreeofeconomicrigour,bothatpolicyandprojectlevel.
58
TASK 3: BARRIERS TO LONG-TERM DECISIONS
Theaimofthistaskistoconsidertheacademicandgreyliteratureonthebarrierstolong-termdecisionmaking,includingbehaviouralsciences,politicaleconomyandriskperception.Threeactivitieshavebeenundertaken.First,thestudyhasundertakenareviewoftheliteratureonthebarrierstoadaptation.Second,amoredetailedreviewhasbeenadvancedinrelationtobehaviouraleconomics.Finally,thestudyhasdrawnupaninitialtableofhowthebarriersmightaffectthemediumtolong-termadaptationdecisionsidentifiedinprevioussections.
Literature Review on the Barriers to adaptation TheIPCC(2001a)definesadaptationas“theprocessofadjustmentinnaturalorhumansystemsinresponsetoactualorexpectedclimatestimuliortheireffects,whichmoderatesharmorexploitsbeneficialopportunities”.Thisdefinitionimplicitlyassumeseffectiveness.Bycontrast,UNDPdefinesadaptationas“aprocessbywhichindividuals,communitiesandcountriesseektocopewiththeconsequencesofclimatechange”(UNDP,2005);andMoserandEkstrom(2010)explicitlyhighlightthatadaptationmayormaynotsucceedinmoderatingharmorexploitingbeneficialopportunities.In2007,theAR4SummaryforPolicymakersofWorkingGroupIIconcludedthatindeedthereare“formidableenvironmental,economic,informational,social,attitudinalandbehaviouralbarrierstotheimplementationofadaptation”(IPCC,2007a,p.19).Barrierscanlimittherangeofavailableadaptationoptionsandcreatethepotentialforresidualdamagesforactors,species,orecosystems.Thisliteraturereviewwillfocusonthebarriersthatconstrainhumanandnaturalsystems’adaptation.Itwillstartbyprovidingsomeconceptualclarifications,thenitwillsummarisethemainfindingsofthreestrandsofliteratureonadaptationbarriersusingthreedifferentanalyticallenses:economic,socialandinstitutional.Withthelattertwostrandsofliteratureweincludeaparticularfocusoninsightsfrom(1)behaviouraleconomicsand(2)politicaleconomy.Barrierstoclimatechangeadaptation–conceptualclarificationsAdaptationbarriersorconstraints(thetermsarefrequentlyusedassynonyms)refertofactorsthatmakeithardertoplanandimplementadaptationactions.OberlackandEisenack(2012)presentfivewaysinwhichbarriersmayimpedetheadaptationprocess:
1. byconstrainingtheavailablemeansforadaptation;2. byhamperingtheuseofavailablemeans;3. byincreasingthecostofadaptation,includingtransactioncosts;4. byreducingtheincentivesforadaptation;5. byincreasingtheincentivesformaladaptation.
Adgeretal.(2009)emphasisethatsomebarriersareneitherabsolutenorinsurmountable,butrathersociallyconstructed,subjectiveandmutable,astheydependontheunderlyinggoalsandvaluesofdifferentdecision-makersacrossdifferentscalesandagencies(e.g.nationalvs.localdecision-makers).Goalsdifferwithinasector,asociety,betweennationstates,andbetweendifferentgenerations;andthechoicebetweenco-existinggoalsistakenbyinstitutionsofcollectiveresponsebasedontheunderlyingvaluesofsociety.
59
Barrierstoadaptationalsovarydependingonthetimehorizon.FactorsthatmightrepresentbarriersorlimitshereandnowmaybeovercomeinthefuturethankstoR&D,changesinriskattitude,changesinrulesorfundingarrangements,communicationandawarenessraising,etc.(seeParketal.,2012;Adgeretal.,2013).Thefocusofthisreviewisonbarrierstobothplannedandautonomousadaptation.Carteretal.(1994)defineautonomousadaptationas”naturalorspontaneousadjustmentsinthefaceofachangingclimate”.Fromtheperspectiveofpublicpolicy,thistendstoincludeadaptationactionstakenbyprivateagentswithoutpolicystimulus,forexamplefarmersswitchingcrops.Plannedadaptationisseenmostgenerallyastheresultofadeliberatedecision,basedontheawarenessthatconditionsmightchangeorhavechangedandthatactionisrequiredtoachieveadesiredstate.FankhauserFromtheperspectiveofpublicpolicy,plannedadaptationtendstobesynonymouswithgovernmentintervention.Plannedadaptationcanbeeitherreactiveoranticipatory.Anticipatoryandreactiveadaptationfacedifferentbarrierssincetheyaregenerallyundertakenunderdifferentcircumstancesandusingadifferentsetofinformation.Forexample,forpublicauthorities,barrierstoanticipatoryadaptation(e.g.uncertaintyandbudgetaryconstraints)maybesetaside/overcomeintheeventofanextremeclimaticshock(e.g.floods),followingwhichclimaticimpactsbecomevisibleandquantifiable(uncertaintyispartlyunfolded)andthoseaffectedexertpressureonthegovernmenttointervene.Moreover,reactivemeasuressuchasemergencyreliefcanbedeliberatelyusedtoboostgovernments’chancesofbeingre-elected(Gaweletal,2012).Intheadaptationliterature,‘good’,‘successful’or‘appropriate’adaptationhasoftenbeendefinedinthecontextofwelfareeconomictheoryanditsunderlyingnormativeprinciples.Accordingtothisframework,barrierstoefficientadaptationbroadlycorrespondtomarketfailures,orthosefactorsthatpreventtheprivatesectorfromdeliveringsociallyefficientadaptation,andthereforejustifygovernmentintervention.Successfuladaptationactionsarethosethatminimisethecombinedtotalofresidualdamagesandcostsofadaptation(seeFankhauseretal.1999;CimatoandMullan,2010),withsuitableadjustmentwhereappropriatefordistributionalweightingacrosstimeandspace,andbarriersarethosefactorsthathampercostminimisation.However,ithasbeenarguedthatthenormativeframeworkunderpinningstandardwelfareeconomictheory,centredasitisonthemarket-governmentdichotomyandonassumptionsofrational,efficientandfairdecisionmaking,maynotdescribereal-worlddecision-makingandoverlookawiderrangeoffactorsaffectingadaptation.Manyanalyticallenseshavebeenusedintheliteraturetodescribebarrierstogoodorsuccessfuladaptation.Thisliteraturereviewwilldescribethemaincontributionsofthedifferentstrandsoftheliteratureonadaptationbarriers.Inthefollowingsection,wewillgothroughthemainbarrierstoclimatechangeadaptation.Theyaregroupedintothefollowingcategories:deepuncertainty;barrierstoeconomicefficiency;social,behaviouralandbiologicalbarriers,and;institutionalbarriers.Thesecategorieshelpdescribetheadaptationbehaviouroftherelevantdecision-makers:individuals,businesses,governmentinstitutions,andtheenvironment.
60
Uncertainty–acommonbarriertoalldecision-makersOnecommonchallengetoalldecision-makersthatrepresentsabarriertosuccessfuladaptationisuncertaintyaroundfutureclimatescenariosandtheirimpacts.Thefutureclimatewilldependpartlyonthefutureemissionstrajectory,butotheraspectsoftheclimatesystemwillalsoinfluenceit.Uncertaintiescanarisefromlimitationsinknowledge(e.g.,cloudphysics),fromrandomness(e.g.,duetothechaoticnatureoftheclimatesystem),andalsofromhumanactions(e.g.,futuregreenhousegasemissions,population,economicgrowthanddevelopment).Theexistenceoftippingpoints,feedbackmechanismsandlimitationsofexistingmodelsmeansthatthereisawiderangeofpossiblefutureclimaticscenarios.Therehasbeenconsiderableprogressinourunderstandingoftheclimatesystem,buttherewillalwaysbeaninherentelementofuncertaintyaboutanyclimatescenario,aboutitsimpactonsocietyandtheenvironmentandthelikelihoodthatitwilloccur.“Deepuncertainty”isdefinedas“theconditioninwhichanalystsdonotknoworthepartiestoadecisioncannotagreeupon(1)theappropriatemodelstodescribeinteractionsamongasystem’svariables,(2)theprobabilitydistributionstorepresentuncertaintyaboutkeyparametersinthemodels,and/or(3)howtovaluethedesirabilityofalternativeoutcomes”(Walkeretal.,2013;Lempertetal.,2003).Thisimpliesthatonecan(incompletely)enumeratemultiplepossibilitiesforthesystemmodel,theprobabilitydistributions,andsetsofvalues,withoutbeingableorwillingtorankorderthepossibilitiesintermsofhowlikelyorplausibletheyarejudgedtobe(Kwakkeletal.,2010).Deepuncertaintycanrepresentabarriertodecisionmakinginadaptationinsofarasitmakesadaptationplanningmoredifficult.Ultimately,itmightpreventagentsfromtakingdecisions,ormakethemchoosetopostponeadaptation.Itmayalsomakethemoptforineffectiveadaptation,ormaladaptation(Halletal.,2007).Deepuncertaintyrequireagentstousecomplexclimaticdataandmakeassumptionsregardingcostsandbenefitsestimation,thechoiceofdiscountrate,riskpreferences,anddealwithissuesofscaleandaggregation.Severalmodelsfordecisionmakingunderdeepuncertaintyhavebeendeveloped,eachwithitsadvantagesandlimitations.Thecomplexityofthesemodelsmayitselfrepresentabarriertoadaptationdecisions.Barrierstoeconomicefficiency:thewelfareeconomicframeworkTheanalyticalframeworkofwelfareeconomictheoryrestsontheassumptionthatdecision-makersareabletotakedecisionsthatmaximisetheirwelfareorutility;andthat,undercertainconditions,themarketisabletoleadtoanefficientprovisionofgoodsandservices.Thereareseveralfactorsthatpreventthemarketfromautonomouslyprovidingandcoordinatingtheappropriatelevelofadaptationandthatthereforeleadtoaninefficientallocationofresources.FankhauserThefollowingmarketfailuresrepresentabarriertoadaptation:Imperfectinformationaboutclimateimpactsreferstothelackofinformationonfutureclimatescenarios,butalsoontheadaptationoptionsavailabletodecision-makersandtheircostsandbenefits.
61
Thereareatleasttwowaysinwhichimperfectinformationcanleadthemarketforclimateadaptationtofail.Thefirstisthatinformationaboutfutureclimatechangeisoftenapublicgood,whichwillbeunderprovidedbyprivateactorsthatcannotcapturethefullsocialbenefitofgeneratingtheinformationthrough,forexample,computermodellingoffutureclimate.Thesecondisthat,ifdifferentagentsintheeconomyholddifferentamountsofinformation(i.e.ifthereisaninformationasymmetry),theninefficienciescanarise,suchasadverseselectionandmoralhazard.Bothofthesearewellknownphenomenaintheinsuranceindustry:underadverseselection,theinsurer’sinabilitytodifferentiatebetween‘good’risksand‘bad’risksmakesitvulnerabletobeingadverselyselectedagainstbybadrisks,inotherwordscustomerswhoseprobabilityofmakingaclaimisrelativelyhigh.Undermoralhazard,takingoutinsurancemakespeoplelesslikelytotakeactionstoinsureorprotectthemselvesthantheyotherwisewouldbe(seeBurbyetal.,1991;Laffont,1995;CimatoandMullan,2010).ExternalitiesandPublicGoods.Actingrationallyintheirowninterest,individualswillbasetheiradaptationdecisionsonprivatecostsandbenefits.However,someadaptiveactionsmighthavethenatureofpublicorquasi-publicgoods(local,nationalorlocal),soindividualactionwillbesociallyinefficient(CimatoandMullan,2010).Thisisthecasewithtransboundarywaters,whenincreasedirrigationinonecountrycreateswaterscarcitydownstream(Gouldenetal.,2009).Examplesofadaptationinvestmentswiththecharacteristicsofpublicgoods3includeinvestmentincertainkindsofinfrastructure(e.g.,flooddefences),R&Dprogrammes(wherethesegeneratespilloversthatcannotbefullyreapedbyprivateagents),monitoringandwarningsystems,andprotectionofecosystems(aswellasclimateforecasts,asmentionedabove).Misalignedincentivesandmissingmarkets.Inthemanagementofphysicalassets,atypicalexampleofthisbarrieristheunevensplitofadaptationcostsandbenefitsbetweenpropertyownersandtenants,whichresultsinlittleornoincentivetoinvesttomakethepropertymoreresilient(CimatoandMullan,2010).Marketstructure.Themarketstructuresinwhichbusinessesoperate(monopoly,oligopolyorperfectcompetition)shapetheincentivesandaffecttheinvestmentdecisionsonclimatechangeadaptation.Leeetal.(2010)describethe‘competitioneffect’andhowdifferentmarketconditionscanaffecttheincentivesforbusinessestoadapt:amonopolistislikelytoputinthehighesteffortstoadapt,sinceitdirectlyrecoversitsprofitlossunderclimatechange;whereasinanoligopoly,competitionandstrategicinteractionmayloweradditionalprofitpotentialforbusinesses,whichtranslatesintolessincentivetoadapt.Economicsectorsvulnerabletoclimatechangesuchasenergyandwaterareoftenpopulatedbystate-ownedmonopoliesorbyregulatednaturalmonopoliesandoligopolies.Marketdistortions.Thiscanbeaneconomicbarrier,aswellasapolicybarrier,anddescribeshowexistingmarketdistortions–oftenpursuedforgoodreasonsbygovernments,suchasrevenueraisingortoachievedistributionalfairness–affectincentivestoadapt.AsdescribedbyFankhauseretal.(1999),whenmarketsignalsaredistorted,peoplemayunder-orover-adapt.Forexample,if,duetomarketdistortions(e.g.priceorincomesubsidies),cropyieldchangesdonottranslateintoincomechanges,farmersmaynotadjusttoachangingclimatebyvaryingthe
3Purepublicgoodsarecharacterizedbynon-excludability, that is, ifapublicgood ismadeavailable tooneconsumer then it is effectively made available to everyone; and non-rivalry in consumption, that is, theconsumptionofthegoodbyonepersondoesnotpreventsomeoneelsefromusingorconsumingthatgood.
62
varietiesofcropstheyplant.Fixedallocationsofwaterresourcesmayleadtoasimilarlackofincentivestoadapt(Fankhauseretal.,1999).Similarly,Leeetal.(2010)showthatiflanduseisinflexible,inaperfectlycompetitivemarketfarmerswillbelesslikelytoadaptduetotheirinabilitytoexpandbusinessalongwiththeiradaptationinvestmentandlittlepotentialtoreapadditionalprofit.Finally,financialbarriersconstrainwhatindividuals,themarketandgovernmentscanefficientlyachieve.Thisisnotamarketfailureperse,butratherlimitswhatisfeasible.AccordingtotheIPCC5thAssessmentReport,existingglobalestimatesofthecostsofadaptationindevelopingcountriesrangefromUS$70billiontoUS$100billionayeargloballyby2050.UNEP(2014)suggestthatthesevaluesarelikelytobeasignificantunderestimate,particularlyintheperiodafter2030;andthatthecostsofadaptationarelikelytwo-to-threetimeshigherthantheestimatesreportedthusfar,andplausiblymuchhigherthanthistowards2050.However,itisreportedthattheamountofpublicfinancecommittedtoactivitieswithexplicitadaptationobjectivesrangedfromUS$23billiontoUS$26billionin2012–2013,ofwhich90percentwasinvestedindevelopingcountries(UNEP,2014)4.Individualswilladaptwithintheircapacitiesasdefinedbytheirinformational,budgetary,institutional,technologicalandotherconstraintsandopportunities(OberlackandNeumarker,2011;Stern,2006;Kuch/Gigli,2007;Osberghausetal.,2010;Hallegatteetal.,2011).Empiricalevidenceshowsthatlackofcredit,andlackofinformationandknowledge,representamajorbarriertoclimateadaptationforfarmersinAfrica(IFPRI,2007;De-GraftAcquaandOnumah,2011;Debalke,2011);andthathouseholds’wealthincreasesthelikelihoodofclimatechangeawarenessandadaptation(Yesufetal.,2008).Deressa(2008)observedthattheageofthehouseholdhead,wealth,socialcapitalandagro-ecologicalsettingshaveasignificantimpactonfarmersperceptionofclimatechange.Social,biophysicalandbehaviouralbarriersEmpiricalevidenceshowsthatindividualsandinstitutionssuchasfirmsdonotalwaysrespectthesimpleaxiomsofrationalchoice.Alongwithmarketfailures,otherbarrierstoadaptationemergefromabroaderconsiderationofhowsocialandbehaviouralfactorsaffectdecision-making,andofbiophysicalconstraintstoadaptationinthenaturalworld.Socialvaluesframehowsocietiesdeveloprulesandinstitutionstogovernrisk,andtomanagesocialchangeandtheallocationofscarceresources(Ostrom2005),andthereforecanhamperorsupportadaptation.Adgeretal.(2009)describebarriersthatareendogenousandemergefrom‘inside’society.Withinasociety/sector/firm,divergentgoalsforadaptationemerge,inpart,fromdifferentattitudestorisk(risk-takersversustherisk-averse),disposition(aprogressiveversusconservativeethos)anddifferentexpectationsoftheadaptivecapacityoffuturegenerations(optimisticversuspessimistic).Berkhoutetal.(2006)showedhowdifferentfirmsoperatinginthesamesector(houseconstruction)adopteddifferentadaptationstrategiestodealwiththesameriskofincreasingriverflooding.
4 These estimates are a combination of Official Development Assistance (ODA) and non-ODA finance bygovernments; Climate Funds earmarked for adaptation; and commitments by Development FinanceInstitutions.ThelattercontributedUS$22billion,or88percent,ofthetotal;bilateraladaptation-relatedaidcommitments by government members of the Organization for Economic Co-operation and Development(OECD)provided9percent;theremaining2percentcamefromadaptationdedicatedClimateFunds(UNDP,2004).
63
Socialandculturalfactorsinfluenceperceptionsofrisk,whatadaptationoptionsareconsideredusefulandbywhom,aswellasthedistributionofvulnerabilityandadaptivecapacityamongdifferentelementsofsociety(GrothmannandPatt,2005;Weber,2006;PattandSchröter,2008;Adgeretal.,2009;Kuruppu,2009;O’Brien,2009;NielsenandReenberg,2010;WolfandMoser,2011;Wolfetal.,2013).Ethical,cultural,riskandknowledgeconsiderationsshapeindividuals’andsocieties’riskperception,theimportancetheyplaceonscientificfindingsasopposedtoindigenousknowledge,andthevaluetheygivetoplacesandtraditions(seeAdgeret.al,2009).Alltheseelementsinfluencehowtheyrespondtoclimatechange.Maddison(2007),forexample,highlightstheimportanceofperceptionandexperienceintriggeringadaptationplanningbyfarmersinAfrica,andhowtransitionalcostsmightindeedarisefrommis-perceptionofclimaticchanges.Thepsychologicalliteratureshowsthatindividualstendtorespondmosttoissues,risksorconcernstheyconsiderasimmediatelyandpersonallyrelevant(MoserandDilling2004;Patonetal.2001),theso-called‘availabilityheuristic’.Peoplerespondnotjusttotheriskitself,butalsotootherpeople’sresponsestorisk(Kaspersonet.al,2003).Dawnayetal.(2005)arguethatpeopletendtoobservethebehaviourofothersand,ifsuccessful,imitateit,especiallyunderambiguity,incrises,andwhenothersareseenasexperts.InAfricafarmersaremoreinclinedtoadaptwhentheyareabletoobserveneighbouringvillages’behaviour,butlessinclinedtolearnfrompeoplebelongingtodifferentethnicgroups(Maddison,2007).Stronglyheldbeliefsandculturalpracticescangreatlyinfluencethewaypeopleperceiveclimatechangeandtherebytheirsubsequentadaptationstrategies(JonesandBoyd,2011;Stafford-Smithetal.,2011;Adgeretal.,2012).Forexample,NielsenandReenberg(2010)reportthatinnorthernBurkinaFasoculturalpracticespreventedoneethnicgroup—theFulbe—fromembracinglivelihood-diversificationstrategiessuchasdevelopmentwork,labourmigrationandgardeningtoreducetheirvulnerabilitytodroughts;whereasanothergroup—theRimaiibe—haveusedsuchstrategies.Similarly,Rademacheretal.(2012)observedthatsocialandculturalnormsconstrainfemalemigrationcomparedtomalemigrationintheNadowlidistrictofGhana,showingthatgendermayindeedrepresentabarrier.Indigenousknowledgemayalsoplayarolebysupportingorpreventinggoodadaptation.Culturalpreferencesfortraditionalversusmoreformal,scientificformsofknowledgeinfluencewhattypesofadaptationoptionsareconsideredlegitimate(JonesandBoyd,2011).CasestudiesfrommultipledevelopingcountriesreportthatsomeactorsviewnaturalphenomenaasbeingcontrolledbyGod,supernaturalforces,orancestralspirits,whicharenotamenabletohumanmanagement(Grothametal.,2013;Mustelinetal.,2010;KuruppuandLiverman,2011;ArturandHilhorst,2012).Socialbarriersalsoincludethesocialfactorsthataffecttheadaptivecapacityofindividualsandcommunities.Gender,age,education,accesstoinfrastructureandfinance,andaccesstomarketsareallelementthataffecttheadaptivecapacity(orlackofit)ofindividualsandsocialsystems.Biologicalandphysicalconstraintsrepresentbarrierstotheadaptationofhumanandnaturalspecies.Theyrefertotolerancelimitsofindividualsandthenaturalenvironmenttoclimatechangeandextremes.Theabilityofnaturalsystemstoadaptmaybehamperedbytherateof
64
climatechangeexceedingthesystem’sabilitytorespond,butalsobytheexistenceofotherstresses,andtheeffectsofhumanactivity(Kleinetal.,2014;CimatoandMullan,2010).Furthermore,physicalconstraintssuchasthelackofcorridorsforspeciesmigrationorsoil/waterscarcitymightconstraintheabilityofthenaturalenvironmentandhumanstoadapttoo.Additionalresearchisneededtoclarifythecapacityofspeciesandcommunitiestomigrateinresponsetoachangingclimate(Kleinetal.,2014).Insightsfrombehaviouraleconomics/scienceThereisbynowahugeliteratureonbehaviouraleconomics,although,byitsverynature,itdoesnotofferaunifiedtheory.Therearetwoparticularlycommonideasprevalentinthisliterature:(a)individualsfacecognitivelimitationsthatcansometimesleadto‘irrational’decisions;and(b)preferencesareformedinasocialcontextwherenorms,perceptionsoffairnessandotherfactorsinfluencedecision-making.Asfaraslong-termdecisionsthataffectclimatevulnerabilityareconcerned,atahighlevelofabstraction,thefollowingkeyinsightsfrombehaviouraleconomicsarecentral.HyperbolicdiscountingHyperbolicdiscountingreferstotheideathatindividualsdonotdiscountthefutureataconstantrate,astypicallyassumedinneoclassicaleconomics,butratherdosoatadecliningratethatcanbeapproximatedby,forinstance,ahyperbolicfunction.Thismeansthatalargerdiscountrateisappliedwhencomparingimmediateconsumptionwithconsumptiondelayedbytperiods,relativetowhenthecomparisonisbetweenconsumptiondelayedbykperiodswithconsumptiondelayedbyk+tperiods.Forinstanceanindividualfacedwithachoicebetween£100todayor£110tomorrowmightwelltake£100today;butifoffered£100in30days’timeor£110in31days’timemightwelltake£110in31days’time.Empiricallytheremaybeaparticularlystriking‘immediacyeffect’,wherebythediscountrateappliedintheinitialmonthsoryearsisveryhigh(Prelec&Loewenstein,1991).Hyperbolicdiscountinghasrathercomplicatedimplications.Buttobeginwithitisimportantnottoconfusethisphenomenon,wherebyindividualsineffectapplyadecliningdiscountratetotheirownlifechoices,withtheacceptedargumentfordecliningdiscountratesinpublicpolicyandprojectappraisal(HMTreasury,2003),whichisbasedonconstantpreferences,butuncertaintyaboutfuturegrowthprospects(Gollier,2002;Weitzman,2001).Hyperbolicdiscountingsuggeststhatpeoplewillberelativelypatientwhenengagedinlong-termplanning–possiblymorepatientthantypicallyassumed–butcertainlylesspatientintheshortterm.Thisraisesthepossibilitythatpeoplearevulnerabletobeingtime-inconsistent:theymakeaplantoundertake,atsomepointinthefuture,someactivitythatwillhaveimmediatecosts(onceundertaken)inreturnforfuturebenefits(theyputthisoffuntiltheirper-perioddiscountratebecomeslowenough),but,whenthetimecomestodoso,theyrenegeontheirplanandpostponetheactivityagain,becausetheirper-perioddiscountrateisveryhigh.Thisislinkedwithideasof(alackof)self-controlandofcommitmentdevicestoovercomethis,whichiswheremanyofthepolicyimplicationsofhyperbolicdiscountingareidentified.Forexample,inhisreviewoftheimplicationsofbehaviouraleconomicsfordevelopment,
65
Mullainathan(2005)pointsoutthatROSCAs5mightserveasacommitmentdeviceforsaversindevelopingcountries,whowouldotherwiselacktheself-controltosavemoneyunderimmediatepressuresforit.Healsosuggeststhatpeoplewithapparentlyhighdiscountratesmaysimplylacktheinstitutionstohelpthemexerciseself-control,whichmeansthattheirdiscountratesoughtnot,perhaps,tobetakenonfacevalue.Moregenerally,ifpeoplewouldliketoexerciseself-controlandmakedecisionswithlong-termpay-offs,butarepreventedfromdoingsobytheirownmyopictendencies,thentheremaybeajustificationforatleast‘nudging’behaviourincertainsituations(socalled‘libertarianpaternalism’;Thaler&Sunstein,2008).Yettheimplicationsofhyperbolicdiscountingforlong-termdecision-makingthataffectsclimatevulnerabilitydonotseemtohavebeenexploredandtheyareratherunclear.Ontheonehand,ifeveryoneexhibitsthesekindsoftimepreferences,thenitisofpotentiallyprofoundimportance,asalldecisionswithlong-termeffectswillbesubjecttothisformof‘bias’,displayedbythepeoplechargedwithmakingthem.Ontheotherhand,itcanberatherdifficulttorelatetheexperimentalcontextsinwhichinsightsonhyperbolicdiscountinghavebeengeneratedwiththetypicaldecisionsinfocusinthisproject.Inparticular,mostinsightsonhyperbolicdiscountinghavebeengeneratedinrelationtoindividuals’lifestyles(e.g.whypeoplefinditdifficulttogiveupsmoking)ratherthanlargeinfrastructureplanningdecisionsinvolvingpotentiallylargenumbersofindividualstaskedwiththinkingrationally.Itmaybethat,ininfrastructureplanning,theinstitutionaldiscountrate–thediscountrateeffectivelyappliedbytheinstitutiontaskedwithmakingdecisions(i.e.aninformalconcept)–isthereforeconstantandconsistentwithstandardtheory.TouseKahneman’s(2011)framework,hyperbolicdiscountingmightbeseenasamanifestationofsubconscious,‘system1thinking’,whileinfrastructureplanningforcesconscious,‘system2thinking’.Lastly,whilethereisplentyofevidencefromlaboratoryexperimentsfortheexistenceofhyperbolicdiscountingand,assuch,ithasbecomeaverywell-knownphenomenon,theevidenceacrossthefullgamutofrelevantexperimentalandfieldstudiesismoremixed(Cardenas&Carpenter,2008).Itisultimatelynotentirelyclearthatthesimplermodelofexponentialdiscountingshouldalwaysberejected.Referencedependence,lossaversionandstatusquobiasAnotherfamousinsightfrombehaviouraleconomicsisthatwhenpeoplemakechoices,eitherinriskyorrisklessenvironments,theircurrentendowmentofgoods–theirreferencepoint–matters.Inparticular,peopledislikelosinggoodsmorethantheylikegaininggoods,aphenomenonthatisoftenknownaslossaversion–particularlywhenitcomestoriskychoice–andispartofthebroaderProspectTheorypioneeredbyKahnemanandTversky(1979).Theeffectcanberepresentedgraphicallybyautilityfunctionwithrespecttothegoodinquestion,whichiskinkedatthereferencepoint(thecurrentendowmentofthatgood),withthefunctionsteeperinthedomainoflossesthaninthedomainofgains.
5 Rotating Savings and Credit Associations
66
Thereareseveralhigh-levelimplicationsofreferencedependenceandlossaversionforlong-termdecision-makingthataffectsclimatevulnerability.Likehyperbolicdiscounting,someofthesearestillvague,however.First,itisworthnotinginthecontextoftimediscountingthatreferencedependenceandlossaversionhavebeenproposedasoneresolutiontothe‘equitypremiumpuzzle’.Thisrelatestotheinabilityofthestandardtheoriesintheeconomicsofrisk(withuniformriskaversion,broadlyspeaking)toexplainthelargedisparitybetweenthereturnsonrisk-freeassetsliketreasurybondsandriskyassetslikestocks.Ithasbeenproposedthatlossaversionmakesindividualslesswillingtotakerisksandhencerequirehigherreturnsonriskyassets(Benartzi&Thaler,1995).Inturn,thishasimplicationsfortheextenttowhichmarketreturnsonriskyassetsarerelevantforpublic-sectordiscountrates,includingforclimate-changeadaptation.Inparticular,itcontributestoargumentsthatquestiontherelevanceofhighratesofreturnonriskyinvestmentsforsettingpublic-sectordiscountrates,suggestingthatlowerratesofreturnonrisk-freeinvestmentsaremorerelevant.Second,itispossibletousetheconceptoflossaversiontomakeamuchbroaderpointaboutthepoliticaleconomyofdecisionsthatcreatewinnersandlosersinsociety.Lossaversionisoneinterpretationofwhyitcanbeespeciallydifficulttoimplementreformsandpolicychangesthatconstituteefficiencygainsoverall,butthattransferresourcesfromoneinterestedgrouptoanother,sincethelosseswillbevaluedevenmorethaninthestandardmodel(Mullainathan,2005).Thissuggestsitmaybebettertodesignreformsthatpreservetherentsofincumbents.Thispointlinkswiththefollowingsectionthatconsidersthemorestandardpolitical-economyliterature.Third,lossaversioncanbeusedtoexplainthephenomenonofstatusquobias(Samuelson&Zeckhauser,1988)asitprovidesanexplanationforwhythedisadvantagesofdeparturesfromthestatusquoloomlargerthantheadvantages(Kahneman,Knetsch,&Thaler,1991).Otherexplanationsofstatusquobiasalsoexist,however,includingtheroleofhabitsindecision-making.Statusquobiashasobvious,ifgeneral,implicationsfordecisionsaffectingclimate
67
vulnerability,wherevulnerabilitywouldbereducedbydeviatingfromthestatusquo.Colloquially,statusquobiasisthoughttobeaparticularafflictionofcautiouspublicservants.Fourth,lossaversionwouldincreasethebenefitsofadaptationmeasuresthatreducevulnerabilitytofutureclimatechange(andcorrespondinglyincreasethecostsofrelateddecisionsthatincreasevulnerability),becausegreatervaluewouldbeplacedontheavoideddamages.Otherissuesofindirectrelevance:thepropensitytocooperateinsocialdilemmasAgeneralinsightfromtheliteratureonexperimentalpublicgoodsgamesisthatpeopleoftencooperatemorethanthestandardconceptionofrationalbehaviourwouldpredict.Inadeveloping-countrycontext,suchexperimentspointtonormsoftrustandreciprocityactingasasubstituteforformalinstitutionsinmanagingcollectivegoods,includingenvironmentalresources(Cardenas&Carpenter,2008).Thequestion,whichseemsrelevantinrelationtosocialprotectionschemesandinsurance,iswhetherthebuildingofnew,formalinstitutionscrowdsoutexistingsocialpreferencesthataidcooperation.Unfortunatelytheevidence,atleastfromexperimentsinbehaviouraleconomics,isunclear.InstitutionalbarriersThewelfare-economicrationaleforpolicyinterventionisbasedontheexistenceofmarketfailures,anddoesnotprecludedoingsoonthebasisofdistributionalinequities,butitimplicitlyassumesaneffective(andfair)governmentresponse.However,thisisnotagivenandvariousliteraturesexaminethepossibilitiesforinstitutionalbarriers.Thesenotablyincludeinstitutionalanalysisandtheeconomicliteratureonpoliticaleconomy.Policyfailuresorbarriersoccurwhenconflictingpolicyobjectivesco-existthatcanleadtomaladaptationorlackofclarity(FrontierEconomics,2013).Forexample,urbandevelopmentplansmaybeundertakenwithouttakingintoaccounttheimpactoncitizens’vulnerability.Thesebarriersoccurwhenthecurrentstructureofinstitutionsandregulatorypoliciesispoorlyalignedtoachieveadaptationobjectives(Craig,2010;Spies,2010;Stillwelletal.,2010;Stuart-HillandSchulze,2011;EisenackandStecker;2012;Huntjensetal.,2012;Herrfahrdt-Pähle,2013).Policyfailurecanalsoariseincasetheproductionofscientificandtechnicalinformationlackssalience,credibility,orlegitimacyintheeyesofcriticalplayersatdifferentlevels(Cashetal.,2003).Otherbarriersconstrainingthecapacityofinstitutionstoperformeffectivelyarethelackofinformationandorprofessionalskills,butalsothelackofaclearmandate(seeKleinetal.2014).Inadditiontopolicyfailures,governancefailuresorbarriersmightoccur.Ifoneoftherolesofgovernmentistoresolveconflictsbetweenagentstoengendercollectiveaction,thentheimportanceofgovernanceinadaptationdecisionsbecomesincreasinglyimportant(Cashetal.,2006).Thesebarriersrefertoineffectiveinstitutionaldecision-makingprocesses.Adaptationtypicallyrequiresmultipleactorsandinstitutionswithdifferentobjectives,jurisdictionalauthorityandlevelsofpowerandresources.Overlappingmandatesandresponsibilitiesofdifferentauthoritiesmayoccur.Barriersarisefromdiversityinresponsibilityandco-ordinationfailurewheresectorsarefragmentedandmanypartiesareinvolvedinadaptationactions
68
(FrontierEconomics,2013),theyoperateinsilosand/orcompeteforresourcesandpolicycontrol(Lockwood,2006).Lehmannetal(2012)arguethathowwellaninstitutionalframeworkissuitedtopromoteadaptationplanningdependsonthehorizontalandverticalintegrationofdecision-making.Verticalintegrationoccursbetweenlocal,regionalandnationaldecisionlevels;whereashorizontalintegrationmayoccurwithinpublicadministrationandbeyond(throughparticipationofbusinesses,science,NGOsandcivilsocietyinthedecisionmakingprocess).Basedonanempiricalanalysis,Lehmanetal.(2012)reportonthebarriersfacedbylocalmunicipalitiesinfourcities,namelyLima,Santiago,BerlinandSangerhausen.Theresultsshowthat,aswellastheproblemofshort-termisminculcatedbyelectoralcyclesanddevelopedbelow,thelackofaclearmandateandresponsibility,ofcoordinationandresources,andlowlevelsofinter-organisationalcooperationallhindereffectiveadaptationplanning.Mainstreamingadaptationintoexistingadministrativetasksandactivitiesisexpectedtoincreasetheincentivesforadaptationplanningbyfacilitatingtheidentificationoflinkstoother(sectoral)policyobjectiveswithapossiblyhigherpoliticalpriorityandpotentialco-benefits(Meashametal.,2011;UNDP/UNEP,2011);andreducethecostsofadaptationplanning(seeFussel,2007;FusselandKlein,2004).However,effectivemainstreamingrequiresaleadorganisationtoensurecoordinationacrosssectors(HuntandWatkiss,2011).Setzetal.(2008)refertothelackofinstitutionalmemoryandinter-institutionalcoordinationasbarrierstoprojectdesign,approvalandevenaccesstointernationalfundsandaidforadaptation.Theauthorsaddthattheoverlappingmandatesofgovernmententitiestendtocreateconflictsandslowadaptiveresponses,forexampleincaseofextremeevents.Lengthybureaucraticprocessesandlackoftransparencyisanimpedimenttofiscalplanningandmayaccesstofinance,whichisparticularlyrelevantforAfricancountries.Finally,thelackofuniversallyapplicableindicatorsforadaptationbenefitsmeansthatmonitoringandevaluatingadaptationoutcomesmightbechallenging.Indicatorsaremeanttoinformdecision-makersabouttheeffectivenessofadaptationactions,contributetosociallearningaboutgoodpractices,holdingagentsaccountablefortheirdecisions,andcommunicatingoutcomes(Lamhaugeetal.,2012).Asassessmentsofadaptationeffectivenesstheycanbemeanttoinformtheprioritisationofadaptationfunds(Stadelmannetal.2011).Poorlydesignedindicatorsmaypreventfundingallocationbydonorsforexample.Inthisrespect,theycanhinderadaptation.InsightsfrompoliticaleconomyThepoliticaleconomyliteratureislargeandvaried.WecanfollowBesley’s(2006)authoritativeliteraturereview,whichseesitsvariousinsightscoalescingaroundthenotionofgovernmentfailure.AccordingtoBesley,governmentfailurecapturestheideathat“therearesystematicreasonswhygovernmentfailstodeliverthekindofservicetoitscitizensthatwouldbeideal”(p45).Butwhatconstitutestheidealservice?OnedefinitionofgovernmentfailureduetoBesleyandCoate(1997)drawsfromthetheoryofmarketfailure:agovernmentfailswhenitsactionspreventtheeconomyfromattainingParetoefficiency,i.e.itwouldintheorybepossibletoreallocateresourcessuchthatatleastonepersonisbetteroffwithoutanyonebeingworseoff.
69
However,justlikethetheoryofmarketfailure,wecouldmaketheobservationthatParetoefficiencyisarelativelyundemandingcriterion,astherecouldbemanyParetoefficientallocations,whichareundesirablefromthepointofviewofdistributionalfairness,forinstancetheyconcentratetoomuchwealthamongtherichandpowerful.Thereforegovernmentsmightalsofailonfairnessgrounds.Twootherfeaturesthatmaybeidentifiedofthepoliticaleconomyliteratureasawholearethat(1)itismainlybasedontheassumptionofrationalindividualbehaviour,incontrasttobehaviouraleconomics,and(2)itisoftendevelopedinthecontextofrepresentativedemocracy(Persson&Tabellini,2000),whichmaybeparticularrelevantinadvancedeconomiesbuthavevaryingdegreesofpurchaseindevelopingeconomies.Theinsightsofthepoliticaleconomyliteratureapplytogovernmentinthebroadestsense,i.e.thelistofgovernmentfailuresenumeratedbelowappliesinprincipletomanyareasofpolicy-making.Thequestioniswhethertheyapplywithgreaterorlesserforcetoclimateadaptation.Thereissomereasontobelievethattheymayapplywithgreaterforce,sinceclimateadaptationinvolvesparticularlylargeuncertainties(ashortageofinformation),andcaninvolveverylong-runbenefitsthatraisequestionsofthepoliticalrepresentationoffuturegenerationsandgovernmentcommitmentproblems(timeinconsistency).Ontheotherhand,relativetootherpolicydecisions,somekindsofadaptationdecisionmayinvolvefewervestedinterests,andinsomecasesgovernmentfailureslikecorruptionmayactuallybiaspolicy-makinginfavouroflargeinfrastructureinvestmentsthatcouldberesilienttofutureclimate.Whatthenarethesourcesofgovernmentfailurethatcouldberelevanttodecisionsthataffectlong-termclimatevulnerability?ImperfectinformationAlongtraditioninpoliticaleconomy,includingnotablytheworkofHayek,arguesthatimperfectinformationontheconsequencesofgovernmentdecisionsputsalimitonthecapabilitiesofstateplanning.Thereisanobvioussenseinwhichmis-estimationofthecostsandbenefitsofdecisionswillleadtogovernmentfailures,relativetoasituationofperfectinformation.Thismaybeparticularlyprofoundinthecaseofclimate-changeadaptation,wherethelong-runcostsandbenefitsofdecisionsarehighlyuncertain.However,themostfundamentalpolitical-economyimplicationsofimperfectinformationtypicallyarisewhendifferentindividualsholddifferentamountsofinformation.Ruta(2014),forexample,looksatagencyproblemsinthegivingofadaptationfinancefromdevelopeddonorcountriestodevelopingrecipientcountries,whichariseinpartbecausethedonorlacksperfectinformationaboutwhattherecipientisdoingwiththemoney,itselfinpartbecauseofthedifficultiesofmeasuringthecostsandbenefitsofadaptationmeasuresinacontextinwhichtheyareintertwinedwithgeneraldevelopment.Moregenerallytherearelikelytobemanyagencyproblemsintheprovisionofinfrastructureindevelopingcountriesjustastherewouldbeindeedindevelopedcountries.Lobbying,corruptionandrent-seeking
70
Anotherimportantinsightfrompoliticaleconomyisthatpublicofficialsdonot,or,atleast,donotonly,actinthepublicinterestlikeabenigndictator,rathertheyaimtoadvancetheirowninterests,sometimesdescribedas‘opportunism’(Persson&Tabellini,2000).GrossmanandHelpman’s(2001)modeloflobbyingportraysagovernmentthataffordssomeweighttothemaximisationofsocialwelfare,ontheonehand,andsomeweighttofinancialcontributionsfromlobbygroupsforthepurposesofresourcingpoliticalcampaigning,ontheotherhand.6Inthesecircumstances,outcomesareskewedawayfromwhatmaximisessocialwelfaretowardstheinterestsoforganisedandwell-resourcedlobbygroups.Whetherthisisinefficientdependsonthemodelofgovernmentfailure:itisnotParetoinefficientunlesstherearecoststolobbyingactivities(overandabovethetransfersthemselves,whicharejustthat),butitmightoftenbethoughtofasinequitable.Whichspecialinterestsprevaildependsinpartontheirabilitytoorganiseandactcollectively(Olson,1965).Whilethismodelismostimmediatelyapplicabletopoliticalsystemswherethereispoliticaldemocracyandwhereitislegitimatetomakefinancialcontributionstopoliticalparties,simplemodelsofcorruptionandbriberyworkinmuchthesameway,inthatgovernmentsauctionoffpolicies,projectsandhowprojectsaredeliveredtothehighestbidder.Indeed,thisinterpretationofeconomicmodelsofpoliticalinfluenceispotentiallythemostrelevantinmanydevelopingcountries.Inprinciple,corruptionandbriberycouldbeemployedtoencourageordiscourageinfrastructureinvestment,butinpracticeorganisedandwell-resourcedspecialinterestsareoftenlocatedamongstthebeneficiariesofinvestmentandthereforeitisclassicallyaningredientin‘whiteelephant’infrastructureprojectsormoregenerallyininfrastructureprojectsthatareinefficientlydesignedordelivered.Adifferenttraditionofpoliticaleconomymodelsthatalsoassessestheeffectsofinfluencefocusesonrent-seeking(Krueger,1974;Tullock,1967,1980).Inthesemodels,politiciansdonotreceivepaymentsfromspecialinterests,nonethelesstheseinterestshaveanincentivetotrytoinfluencepoliticaldecisionsanddoingsohasanopportunitycostintermsofproductivelabour.Politiciansinthesemodelsaretypicallyrent-seekingratherthanoffice-seeking.Again,whetherrent-seekingleadstogovernmentfailureiscomplicated.Inandofitselfitiscostly,buttheoutcomemightsometimesprovidebenefitsinexcessofcosts.Alsobelongingtothisbroadthemeisresearchontheincentivesofbureaucrats,asopposedtopoliticians.Niskanen(1971)proposedthebudget-maximisingmodelofbureaucraticbehaviour,whichsuggeststhatself-interestedbureaucratsaimtomaximisethebudgetsoftheiragenciesinordertoincreasetheirpowerandwealth,evenifthepoliticiansforwhomtheyactasagenthavethepublicinterestinmind.Thattheyenjoythispossibilityisduetothetypeofinformationalasymmetrymentionedabove:agenciesarepresumedtobetterknowtheircostsandbenefitsthanthepoliticianswhorelyonthem.Qualityofdecision-makingTheaforementionedmodelsdonottakeintoaccountaretheintrinsicqualitiesofpoliticalleadersandpolicy-makers,asidefromtheirtendencytobeself-interested.However,some
6 Other means of lobbying exist, such as information.
71
policy-makersmayproduce‘betterprojects’thanothers,inageneralsense,orelsetheyarebetteratcarryingouttheircitizen’swishes.Thisisasimplesourceofgovernmentfailureinthesensethatimprovementscouldbeobtainedbyimprovingthequalityofpolicy-makers.Incontrasttomodelsofinfluence,corruptionandrent-seeking,thisargument,broadlyspeaking,relatestothehumancapitalattainmentofpolicy-makers.PoliticalfailuresindemocraciesAbasicsourceofpoliticalfailureindemocraciescanariseundersimplemajorityvotingandisbestunderstoodasfollows:simplemajorityvotingmerelycountsthenumberofvotersinfavourof,oragainst,aparticularpolicychangebutignorestheintensityofpeople’spreferences.If,forexample,amajorityofpeoplestandtogainasmallamountandyetaminorityofpeoplestandtoloseagreatdeal,thenmajorityvotingwillfavourtheformeroverthelatter,eventhoughaggregationofpreferencesinthestandardeconomicway(evenwithoutconsiderationsoflossaversion)wouldtendtoworkagainstthis.Notethiseffectstandsincontrasttowhatmightusuallybeexpectedtofollowfromspecial-interestcapture,discussedaboveunderpoint2.Anotherformofpoliticalfailurecanarisefromso-called‘log-rolling’,i.e.thetradingoffavoursbetweenpoliticiansinorderthateachgetsthepoliciespassedthats/hewants(thisissometimesspecificallycalled‘distributivelog-rolling’andtheoriginalideaisfromBuchanan&Tullock,1962).Suchsituationscan–attimes,i.e.notinevitably–leadtotoomanypublicprojectsbeingimplemented.Inthecontextoflong-termdecision-makingthataffectsclimatevulnerability,ifitcanbearguedthattoolittleweightisbeingplacedontheinterestsoffuturegenerationswholacktheabilitytovote–anotuncontroversialclaimthatisatthecentreofthediscountingdebate–thenthisisalsoapoliticalfailurethatcouldleadtoinsufficientadaptationtofutureclimatechange.Folkeetal.(1998)andYoung(2003)discussthebarrierstosustainableresourcemanagementstemmingfromtheconflictbetweenshortelectoralcyclesandlong-termplanningneeds.CommitmentandtimeinconsistencyTheworkofKydlandandPrescott(1977)focusedattentionongovernmentfailures,whichcanarisefromtheinabilityofapoliticianorpolicy-makertocommitaheadoftimetoaparticularcourseofaction.Thisisbecauseitcanberationalforapolicy-makertolaterchangecourse,evenonethatisbenevolentandisnotsubjecttotheneedtogetre-elected.Inasimplemodelofthiskindoftime-inconsistencyinpublicpolicy,agovernmentthatisbenevolentinthesenseoftryingtomaximisesocialwelfaremustchoosewhethertoimplementapolicytodayand/ortomorrow.Societyreceivesbenefitsandcostsfromthepolicy,aswellasbeingabletomakeprivateinvestmentstodaythatpayofftomorrow.Themodelcanbesetupinsuchawaythat,eventhoughitwouldbebestforsocietyifthegovernmentimplementedthepolicytomorrowandcitizensmadeprivateinvestmentstoday,thegovernmentwouldchoosenottoimplementthepolicytomorrowuponknowingthatcitizenshavemadetheinvestmenttoday.Withrationalexpectations,citizensdon’tthenmaketheinvestment.
72
Inthissimpleexample,theonlythinglinkingtodayandtomorrowisinvestment,butotherpolitical-economymodelsintroducepolicyandpoliticallinkages.Theformertypeoflinkagemakesthesuccessofthepolicytomorrowdependentonwhetheritisimplementedtoday,whilethelattertypeoflinkageintroducespoliticalsurvivalfromtodaytotomorrowasaconsideration.Policylinkageshavebeenusedtoexplainwhypoliticiansmakestrategicchoicestoconstraintheactionsoftheirsuccessors.Thedesiretosurviveinpoliticaloffice,ontheotherhand,canleadpoliticianstopostponeorbringforwardpoliciesdependingonthesituationandthiscanleadtoadeviationfromwhatisefficientorequitable.
Mapping of Barriers to Decisions Thesectionsabovehighlightthepotentialbarrierstoadaptation.However,thisprovidesatheoreticalperspective.Akeyissueforthecurrentstudyistotranslatetheseissuesintoamorepracticalsetting,andthenlookatpotentialsolutions.Toadvancethisanalysis,thestudyhasmappedthepotentialbarriersidentifiedabovetothepriorityareaswehaveidentifiedformediumtolong-termadaptationdecisions.Thisisshownbelow.Thetablepresentsthemainbarrierstoclimatechangeadaptation–focusingonspatialplanning,serviceandinfrastructuredelivery-andproposessomepossiblesolutions.
73
Reviewofbarrierstoadaptationplanninganddecision-makingDecisions Marketfailures PolicyFailures Governancefailures SocialandBehaviouralbarriers ExamplesofSolutionsEarlydecisionsthatcanlock-invulnerabilityUrbanandSpatialPlanning
InformationfailureExternalitiesClubgoodsMarketdistortions(e.g.priceofhousesonfloodproneareasdoesnotreflectrisk)Misalignedincentivesforpeoplelivinginurbanareas(e.g.tenantsvs.owners)
Regulatorybarriersstemmingfrommultipleframeworksapplyingtovarioussectors(landuse,housing,transportation,publicfacilitiesandservicesetc.)LimitedcoverageofornomandatoryactionwithinlegislationandregulationsConflictingpolicies/priorities(e.g.pressureforurbandevelopment/housingcounteractwithadaptationgoals/reducingvulnerability)LackofclearrolesandresponsibilitiesofactorsinvolvedinadaptationSpatial/UrbanplansarepoorlyenforcedLimitedadaptationforexistingbuildings/assets
Institutionswitharoletoplayinclimatechangeadaptationarepoorlyintegrated,bothbetweensectorsandacrossspatialscalesRangeofdecisionmakersinvolved(developers,buildingcompanies,insurancecompanies,propertyownersandoccupants)whobasetheirdecisionsondifferenttimescalesandgoalsLackofclarityandaccountabilitymechanismsforadaptationdecisionsSomeadaptationswiththecharacteristicsofclubgoodsrequiringhighcoordinationandjointactions.Highlybureaucraticprocessesmakedecisionmakinglengthy
Cognitivebiasesofpolicymakers-urbanplanners,aswellasurbancitizensLimitedadaptivecapacityofplanningauthorities(time,moneyandhumanresources)Limitedadaptivecapacityofurbaninhabitants(accesstofinance-includinginsurance,information)InertiaandprocrastinationofbothplannersandurbaninhabitantsDemographicandsocio-economicphenomena(e.g.migration,populationgrowth)Socialnorms(e.g.socialcapital)
ReviewandharmoniseregulatoryframeworksgoverningurbanplanningConsideracross-sectorstrategyformainstreamingadaptationactionsintoexistingurbanmanagementactivities,includinglanduseplanning,transportation,water,andenvironmentalpolicy.Thestrategyshoulddefinerisks,setpriorities,competences,andactionsfordifferentactorsConsiderestablishingaleadgovernmentdepartmentplayingacoordinatingroleImproveunderstandingofandinformationoncostsandbenefitsofadaptivemeasuresforthebuiltstockintheurbanenvironmentCapacitybuildingforplanners.Considerdevelopingguidance.AppropriatestaffingofplanningagenciesDesigninformationcampaignsthatusesocialnormsforbehaviourchangee.g.byinformingindividualsaboutdesirablebehaviourofothers,possiblybyemphasizingtherealstatisticalprobabilityofdifferentrisks
74
Decisions Marketfailures PolicyFailures Governancefailures SocialandBehaviouralbarriers ExamplesofSolutionsIntegratedWaterResourcePlans
InformationfailureMarketdistortionsandexternalities(e.g.waterpricing)Differentopportunitycostofwatertodifferentusers
Conflictingpolicies/priorities(agriculture,energy,domesticwateruse,recreation)Lackofintegratedregulatoryframeworksapplyingtodifferentwateruses(agriculture,energy,urbanplanning)Lackofclearrolesandresponsibilitiesofactorsinvolvedinplanningandadaptation
Widerangeofstakeholdersinvolvedinwatermanagementanduse,plusmultipleuses(irrigation,energy,domesticconsumption)contributetocomplexdecision-makingprocess.Differentactors/agencieslikelytooperateinsilosCoordinationonvastspatialscalerequired(e.g.upstream/downstream)
Cognitivebiasesofpolicymakers,planners,aswellasurbancitizensLimitedadaptivecapacityofplanningauthorities(time,moneyandhumanresources)Limitedadaptivecapacityofwaterusers(e.g.accesstofinance,information)InertiaandprocrastinationofbothplannersandwaterusersSocial/customarybeliefsandwatermanagementpractices
ImproveunderstandingofandinformationoncostsandbenefitsofadaptivemeasuresReviewingofregulatoryframeworkstoensurepolicycoherenceConsideracross-sectorstrategyformainstreamingadaptationactionsintoexistingwatermanagementactivities,includinglanduseplanning,agriculture,energy,andenvironmentalpolicy.Thestrategyshoulddefinerisks,setpriorities,competences,andactionsfordifferentactorsConsiderestablishingaleaddepartmentplayingacoordinatingroleonIWRMCapacitybuildingforplanners.Considerdevelopingguidance.CommunicationandengagementplantochangeusersbehaviourIntroducedemand-drivensolutions:low-flowappliances;moreeffectiveuseofwaterinagriculturalandindustrialprocesses;smartmetersandintelligentpipeworktorestrictaccessandreduceleakage;andmeteringandpricingstrategies.
75
Decisions Marketfailures PolicyFailures Governancefailures SocialandBehaviouralbarriers ExamplesofSolutionsCoastalManagementPlanning
InformationfailureMissingmarkets(ecosystemsservices)Clubgoods/publicgoods
Poorintegrationofcoastalplansandregulationsintolocal/regionalspatialplansandregulationsOverlappingmandatesofdifferentagenciesandgovernmentinstitutionsMultipleregulatoryframeworksapplying(e.g.infrastructure,buildings,habitatsandlivelihoods)andpoorlyintegratedConflictingpriorities(environmentalpreservationvseconomicdevelopmentandhousing)
Widerangeofstakeholdersanddecisionmakersinvolved(e.g.environmentprotectionagency,localgovernments,localcommunities,localbusinesses,insurancecompanies)PoorcoordinationbetweenagenciesresponsibleforadaptationHighlevelofcoordination/localfundingmechanismsrequiredforclubgoods(e.g.localseawalls)
Cognitivebiasesofpolicymakers,planners,aswellaslocalcommunitieslivingincoastalareasLimitedadaptivecapacityofplanningauthorities(time,moneyandhumanresources)Limitedadaptivecapacityofcommunities(lackofinfo,resources)InertiaandprocrastinationofbothplannersandcoastsinhabitantsLimitedadaptivecapacityofthenaturalenvironment
CoastalmanagementplanningintegratedinbroaderspatialmanagementplansHarmonisationofregulatoryframeworksapplyingtoadaptationincoastalareas(tourism,housing,environment,buildings,infrastructure)Clarityarounddifferentagencies’rolesandresponsibility.Considerselectaleadinstitution/agencywithclearmandateTargetedcommunicationandengagementstrategieswithlocalcommunities,usinglocalsocialnormstochangebehaviourCapacitybuildingandtrainingforplanners
Decisions Marketfailures PolicyFailures Governancefailures SocialandBehaviouralbarriers ExamplesofSolutionsLandUseandAgriculturalDevelopmentPlans
InformationfailureExternalitiesHightransaction/coordinationcostsMarketdistortions(e.g.subsidies)
Multipleregulatoryframeworks(watermanagement,agriculture,environmentalregulations,spatialplanning)Internationalregulationsandmarketsaffectingdomesticproductionandprices,i.e.incentivestoadapt
Largenumberofdecisionmakers(farmers)posecoordinationchallengesLackofcoordinationbetweenrelevantgovernmentagencies(e.g.Agriculture,Forestry)
CognitivebiasesofpolicymakersCognitivebiasesoffarmersLackofadaptivecapacityoffarmers(info,accesstotechnology,accesstofinance)CustomarylandtenureandlandmanagementpracticesHabitandtaste(e.g.switchingtomoreclimateresilientcropsandchangingdietmaybedifficult)
Clarityofmandates,rolesandresponsibilityofdifferentagenciesRemovalofmarketdistortions(e.g.subsidies)affectingadaptationdecisionsAlignmentandharmonisationofdifferentregulatoryframeworks(onwater,environment)Consideracross-sectorstrategyformainstreamingadaptationactionsintoexistinglandmanagementactivities,includinglanduseplanning,agriculture,andenvironmentalpolicy.Thestrategyshoulddefinerisks,setpriorities,competences,andactionsfordifferentactorsInformationcampaignedtailoredtofarmerstoimproveunderstandingofcostsandbenefitsofadaptationmeasures
76
Decisions Marketfailures PolicyFailures Governancefailures SocialandBehaviouralbarriers ExamplesofSolutionsSocialProtectionPolicy
PublicGoodFiscalspace
Adaptation,DRRandsocialprotectionpoliciesandobjectivesnotaligned/sufficientlyintegratedTradeoffbetweenshortterm(DRR,povertyalleviation)andlongtermneeds(climatechangevulnerability)Conflictingpoliciesandregulatoryframeworks(e.g.economicandsocialpolicyobjectives)SPtargetpeoplewhoarecurrentlyvulnerable–lessfocusonpotentialvulnerablepeopleinthefutureVulnerabilitytoclimatechangenotexplicitlyconsideredinpolicies
CrosscuttingnatureofSocialProtectionpolicies(housing,services,directtransfers)andmultipledecisionmakersinvolvedOverlappingmandatesofdifferentagencies–lackofcoordinationandworkinginsilosPossiblecomplexityofsomemechanisms(index-basedinsuranceschemes)orriskofheavygovernancestructure(socialfundsforcommunitybasedadaptation)
CognitivebiasesofpolicymakersCognitivebiasesofbeneficiariesofsocialprotectionschemes–inertia,procrastination,short-sigheddecisionmakingLackofcapacityofresponsibleagencies(staff,time,resources)Lowadaptivecapacityofrecipientsofsocialprotectionmeasures(typicallythemostvulnerableinsociety)
Clarityoflinkbetweenadaptivecapacityandsocialprotectionschemes–ccvulnerabilityexplicitlyaddressedConsideracross-sectorstrategyformainstreamingadaptationactionsintoexistingsocialprotectionplansandactivities.Thestrategyshoulddefinerisks,setpriorities,competences,andactionsfordifferentactorsEnhancedemphasisonpreventivemeasurestoincreaseadaptivecapacityCommunicationstrategytargetedtothepoorandmostvulnerablearoundccrisks
77
EarlyinvestmentthatexposedtofutureclimaterisksDecisions Marketfailures PolicyFailures Governancefailures SocialandBehaviouralbarriers ExamplesofSolutionsNewCriticalInfrastructure(e.g.publicwatersupply,hospitals,waste-watertreatment)
InformationfailurePublicgoodsgeneratingpositiveexternalities(e.g.health),naturalmonopolies(e.g.energydistribution),andmeritgoods(e.g.water)Marketdistortions(e.g.watertariffskeptinefficientlylow)Misalignedincentives(dependingonhowconcessioncontractsarebuilt)Limitedpublicfiscalspace
Overlappingpolicies/prioritiesandexistenceoftrade-offs(e.g.betweencontinuityofsupplyandaffordability;developmentandvulnerability)GovernmentagencieslackingaclearmandateonadaptationIncentivestoadaptnotbuiltintoPPPcontractsPoorlydefinedresponsibilities,orlackofcoordinationbetweenvariousoperators(particularlyrelevantduetointerconnectivitybetweentheinfrastructureassets)
Multipleandcomplexlevelsofdecisionmakinginvolved(designers,owners,operators,users)Lengthydecision-makingprocessRiskofpoliciesbeingdesignedandimplementedinsilobydifferentagencies/decisionmakersLackofleadagency,andlackofclearlineofaccountabilityforadaptationRiskofcorruption/misuseoffunds
Cognitivebiasesofdecisionmakersresponsiblefordecidingoninfrastructureinvestment(e.g.useofcomplexclimaticinfo,lackofclarityaroundcostsandbenefitsofoptions)Perceptivebiases(e.g.recentstress)Self-interestofdecisionmakers(e.g.elections)Lowadaptivecapacity(e.g.noaccesstotechnology,finance,information)ofdifferentagentsInertiaandprocrastinationpreventingpeoplefromusingpublicservicesandinfrastructuremoresustainably
ImproveunderstandingofclimaticthresholdsimpactingontheperformanceofdifferentinfrastructureReviewandharmoniseexistingregulatoryframeworksforinterconnectedinfrastructureassetsReviewregulationsanddesignstandardstoincorporateclimatechangeConsideracross-sectorstrategyformainstreamingadaptationintoinfrastructureplanningandactivities.Thestrategyshoulddefinerisks,setpriorities,competences,andactionsfordifferentactorsConsiderselectingaleadorganisation/agencyplayingacoordinatingandsupervisoryroleIntroduceperformancestandardsinprocurementwhichaccountforclimatechangerisksAllocateclimatechangerisksbetweenpublicandprivateactorsinamoretransparentwaye.g.inconcessionagreementcontractsIntegrationandclarificationofrolesandresponsibilitiesofdifferentjurisdictions(local,national,international)ConsiderintroducingperformancestandardsinprocurementwhichaccountforclimatechangerisksUnderstandindividuals’tolerancetorisksresultingfromthefailureofinfrastructure,andtheirwillingnesstopaytoreducethoserisks.Tariffsreviewcouldbemadeaccordingly.Designinformationcampaignsthatusesocialnormsforbehaviourchangee.g.byinformingindividualsaboutdesirablebehaviourofothers,possiblybyemphasizingtherealstatisticalprobabilityofdifferentrisksInformationcampaignsandpublic’sexpectationmanagementofinfrastructureperformanceunderclimaticstress
78
Decisions Marketfailures PolicyFailures Governancefailures SocialandBehaviouralbarriers ExamplesofSolutionsNewhydroorlargedams
UncertaintyandmissinginformationonclimatevariabilityandimpactsonriverflowsHigheruncertaintyforassetswithlong-termlife,about100yearsNaturalmonopolygeneratingexternalities(irrigation,floodmanagement,recreation)Marketdistortions(e.g.tariffskeptinefficientlylow)Misalignedincentivesofvariousstakeholders(benefitsofadaptationreapedbydifferentstakeholdersatdifferenttimes)
Lackofinstitutionalframeworkand/orinvestmentstrategythatallowforclimatechangetobeincorporatedintoinvestmentdecisionsLackofintegrationorconfusionbetweenpolicies,prioritiesandtrade-offs(e.g.agriculture,irrigationandenergypolicies)Poorstandards(e.g.design)adsafeguards(e.g.environmental)and/orlackofenforcementPoorlydefinedresponsibilities,orlackofcoordinationbetweenthevariousagentsresponsiblefordesigning,operatingandmanaginghydroIncentivestoadaptnotbuiltintoPPPcontractsCross-boundaryregulations(e.g.forexportprojects)
Complexnetworkofstakeholdersandvestedpartiesinvolvedinthedecisionmakingprocess(plannersandregulators,designers,owners,financiersandlocalcommunities)allplayingaroleinsupporting/constrainingadaptationLengthydecisionmakingprocesspreventingtimelyresponse
Cognitivebiasesofdecisionmakersresponsiblefordecidingoninfrastructureinvestment(e.g.useofcomplexclimaticinfo,lackofclarityaroundcostsandbenefitsofoptions)LackofclarityaroundbenefitsfromadaptationleadingtoinertiaandprocrastinationLowaccesstotechnologyLowaccesstofinanceLowaccesstoinformationLackofhuman,timeandfinancialresourcesofinstitutionsCustomarylandmanagementactivities(e.g.somecropscultivatedinthereservoirareamayincreasesedimentationissues)
Improveunderstandingofclimatechangeimpactonriverbasins,andplants’runoffelasticitytoclimaticstressDevelopguidelinesfordevelopersonwhatclimaticinfoshouldbeusedforEIA,minimumenvironmentalflowsetc.ReviewregulationsanddesignstandardstoincorporateclimatechangeAllocateclimatechangerisksbetweenpublicandprivateactorsinamoretransparentway(e.g.inconcessionagreements)Improvemonitoringofclimate-triggeredevents(floods)Infocampaignsforlocalcommunitiesonwhattodoincaseofextremeevents(e.g.floods)Considerintroducingperformancestandardsinprocurementwhichaccountforclimatechangerisks
79
Decisions Marketfailures PolicyFailures Governancefailures SocialandBehaviouralbarriers ExamplesofSolutionsNewcriticalnodes,e.g.bridges
InformationfailurePublicgoodsExternalitiesMisalignedincentives(dependingonhowconcessioncontractsarebuilt)Hightransactioncosts(communicationandsharinginfo)
Confusionbetweenpolicies/priorities,existenceoftradeoffs(e.g.continuityvsaffordabilityofservices)IncentivestoadaptnotbuiltintoPPPcontractsGovernmentagencieslackclearregulatorymandateonadaptationPoorlydefinedresponsibilities,orlackofcoordinationbetweenthevariousoperators(particularlyrelevantduetointerconnectivitybetweentheinfrastructureassets)Cross-boundaryregulationsmightapply(acrossdifferentjurisdictions)
Widerangeofactors(privateandpublic)involvedinthedecisionmakingthroughoutthelifeofaproject(financing,construction,maintenanceandoperation)Multiplevestedpartiesindifferentjurisdictionsmakecoordinationandcollaborationmorecomplex
Cognitivebiasesofdecisionmakersresponsiblefordecidingoninfrastructureinvestment(e.g.useofcomplexclimaticinfo,lackofclarityaroundcostsandbenefitsofoptions)Users’lowcapacitytoadaptduringemergencies/extremeevents
ReviewregulationsanddesignstandardstoincorporateclimatechangeConsiderintroducingperformancestandardsinprocurementwhichaccountforclimatechangerisksAllocateclimatechangerisksbetweenpublicandprivateactorsinamoretransparentway(e.g.inconcessionagreements)Integrationandclarificationofrolesandresponsibilitiesofdifferentjurisdictions(local,national,international)InformationsharingandcollaborationacrossjurisdictionsImprovepreparednessforemergenciesanddisastersContinuousmonitoringImproveunderstandingofpublic’swillingnesstopayforinfrastructureresilienceInformationcampaignsandpublic’sexpectationmanagementofinfrastructureperformanceunderclimaticstress
Forestrymanagement
PublicgoodExternalitiesMissingmarkets(e.g.forecosystemservices)Marketdistortions(distortedpriceshamperingthesustainableuseofnaturalresources)
Co-existenceofmultipleframeworksforlanduseandagriculture,coastalzonemanagementandwatermanagement,allregulatingthenaturalenvironmentConfusionbetweenrolesandresponsibilitiesofdifferentministries(e.g.ofenvironment,water,forestry)
UsuallycomplexnetworkofpartiesinvolvedinthedecisionmakingofpoliciesonforestryDifficult/expensivemonitoringIllegalactivities(e.g.illegallogging)
CognitivebiasesofdecisionmakersfacedwithgreatuncertaintyaroundclimateimpactsandadaptivecapacityofthenaturalenvironmentHumansystems’behaviouralpatternsexertadditionalpressureonthenaturalenvironment(e.g.nosustainableuseofresources,illegallogging)Socialnormsandcustomarypractices
ImproveinfooninterdependencybetweenmanmadeadaptationandthenaturalenvironmentImproveinfoandcommsonclimatechangeimpactsonecosystems’servicesClarifyrolesandresponsibilitiesofdifferentgovtdepartmentsConsidercommunitydrivenadaptationoptionsConsiderPESschemes
80
Thedecisionsinthetableinvolvemultipleactorswhocancontributeorhamperadaptationatdifferenttimesinthedecision-makingprocesses.Plannersandregulators,theprivatesector,andthepublicallplayaroleinmakingtheurbanenvironment,servicesandinfrastructuremoreorlessresilienttoclimatechange.Barrierstoadaptationlimittheabilityofeachactortoincorporateclimatechangerisksintotheirdecisions,andthereforetoundertaketheappropriatelevelofadaptation.Foreachdecision-maker,barriersusuallyincludeacombinationofeconomic,institutional,socialandgovernance-relatedfactors,andthusrequireacombinationofinstrumentstoaddressthem.Urbanandspatialplanningisatechnicalandpoliticalprocessconcernedwiththeuseoflandanddesignoftheurbanenvironment,services,andtransportationanddistributionnetworks.Bydeterminingthespatiallocationandnumberofdevelopments,andbyaffectingthedemandforinfrastructureservices,decisionsonurbanplanningareabletoinfluencethevulnerabilityorresilienceofthebuiltenvironmentanditsinhabitants.Awiderangeofbarriersexiststhatpreventurbanplannersandinhabitantstoadapttoclimatechange:theseincludecomplexdependencies,assignmentofresponsibilitiesandtheexternalitiesinvolved,behavioralbarriersandinertia,andthepooralignmentofdifferentregulatoryframeworksthatarerelevanttourbanplanning.Incentivestoadapttoclimatechangecanbeincorporatedintobuildingregulationsandcodesinordertoreducetheexposureoftheurbanenvironmentanditscitizenstoclimatestressesandextremeevents(e.g.floods,heat-waves).Similarbarrierspreventadaptationinothersectorialplanningsuchascoastalmanagement,waterresourcesmanagementandagriculturalplanning,whicharegreatlyaffectedbythecurrentuncertaintyaroundtheimpactofclimatechangeonthenaturalenvironment(e.g.futureavailabilityandqualityofwater),theintegratednatureofsectorsandthemultipleregulatoryframeworksapplyingtothemanagementofnaturalresources(e.g.irrigation,energygenerationanddomesticconsumption),thelackofmarkets(e.g.forecosystemservices),andevenculturalnormsandpractices(e.g.customarylandtenuresystemsandwatermanagementapproaches).Inallcases,barrierscanbeaddressedthroughsupply-typesolutions(e.g.changeinregulation,codes,betterintegratedregulatoryframeworks,andclarityonrolesandresponsibilityofdifferentagencies)aswellasdemand-type(e.g.throughamoresustainableuseofresourcesandservices).Largeinfrastructureincludesassetswithlong-termlifespan,whoareexpectedtoperformundercurrentandfutureclimaticscenarios(newbuiltinfrastructure,dams,criticalnodes).Inthiscase,incentivestoadaptationcanbeincorporatedintocontractualagreements,suchaspublic-privatepartnership(PPP)agreements.Theseagreementsdeterminetherolesandresponsibilitiesofdifferentactorsindesigning,building,operatingandmaintainingtheassets,andcontainprovisionsonrisksharingbetweenthegovernmentandtheprivatesector.PPPagreementslieonthefundamentalprinciplethattheprivatesectorshouldassumethoserisksthatitisbestsuitedtomanage.ThereareawiderangeofPPPcontracts,includingforexamplebuild–own–operate–transfer(BOOT),aprojectfinancingarrangementwhereinaprivateentityreceivesaconcessionfromthepublicsectortofinance,design,construct,andoperateafacilitystatedintheconcessioncontract;ordesign–build–finance–operate(DBFO),whichisverysimilartoBOOTexceptthatthereisnoactualownershiptransfer.Theowneroftheprojectultimatelybearstheriskofmala-adaptation,whichinthecaseofBOOTistheprivatesectorforthedurationoftheconcessionagreement,andtheGovernmentafterthat.
81
Regulatorybodiescansettechnicalstandardstoinfluencetheresilienceofnewly-constructedinfrastructure.However,privatecompaniesmaylackthenecessaryincentivestoretrofitexistingstructuresasthebenefitsmayoccuraftertheircontactshavecometoterm.Giventhehighinterconnectivityofvariouscriticalinfrastructureassets,adaptationshouldbeundertakentopromotesystemsresilience,ratherthansectorresilience,andaddresssystemfailurerisks.Importantly,somedamagemaynotbeavoided(ortoocostlytobeavoided),thusitisadvisedthatinfrastructureoperatorsgetabetterunderstandingofusers’willingtopayforserviceatagivenlevel.Collaboration,planningandsharingofinformationbetweensectorswouldalsoberequiredtoensuresystemsresilience.Inthecaseofcriticalinfrastructure,analysinginterdependenciesmaybechallengingasitrequiresadeepunderstandingoneachcomponentofthesystem,andofthelinksbetweensystemsonawiderscaleandacrossjurisdictions.Giventhelargenumberofdecisionmakersinvolved,governancebarrierscanbesignificant.
82
REFERENCES EarlyliteraturereviewanddevelopmentreviewAfDB(AfricanDevelopmentBankGroup)(2011).ClimateScreeningandAdaptationReview&EvaluationProcedures,AfDB,Tunis.Annandale,G.W.2013.QuenchingtheThirst:SustainableWaterSupplyandClimateChange,CreateSpace,Charleston,SCBoin&McConnell,2007‘PreparingforCriticalInfrastructureBreakdowns:TheLimitsofCrisisManagementandtheNeedforResilience,JournalofContingenciesandCrisisManagementVolume15,Issue1,pages50–59,March2007).Dasgupta,P.,J.F.Morton,D.Dodman,B.Karapinar,F.Meza,M.G.Rivera-Ferre,A.ToureSarr,andK.E.Vincent,2014:Ruralareas.In:ClimateChange2014:Impacts,Adaptation,andVulnerability.PartA:GlobalandSectoralAspects.ContributionofWorkingGroupIItotheFifthAssessmentReportoftheIntergovernmentalPanelonClimateChange[Field,C.B.,V.R.Barros,D.J.Dokken,K.J.Mach,M.D.Mastrandrea,T.E.Bilir,M.Chatterjee,K.L.Ebi,Y.O.Estrada,R.C.Genova,B.Girma,E.S.Kissel,A.N.Levy,S.MacCracken,P.R.Mastrandrea,andL.L.White(eds.)].CambridgeUniversityPress,Cambridge,UnitedKingdomandNewYork,NY,USA,pp.613-657.Davis,A.P.,Gole,T.W.,Baena,S.&Moat,J.TheImpactofClimateChangeonIndigenousArabicaCoffee(Coffeaarabica):PredictingFutureTrendsandIdentifyingPriorities.PLoSONE7,e47981(2012).DFID(2014),EarlyValue-for-MoneyAdaptation:DeliveringVfMAdaptationusingIterativeFrameworksandLow-RegretOptions,DFID,London.Dixit,A.K.,Pindyck,R.S.,(1994).InvestmentunderUncertainty.PrincetonUniversityPress,Princeton,NJ.DowningT(2012).Viewsofthefrontiersinclimatechangeadaptationeconomics.WIREsClimChange2012,3:161–170.doi:10.1002/wcc.157ECONADAPT(2015).TheCostsandBenefitsofAdaptation.ResultsfromtheECONADAPTProject,ECONADAPTconsortium,availableathttp://econadapt.eu/.GoT(2014).AgricultureClimateResiliencePlan,2014–2019.GovernmentofTanzania,MinistryofAgriculture,FoodSecurityandCooperatives(MAFC).PublishedSeptember2014.DarEsSalaamTanzania.Hallegatte,S(2009).Strategiestoadapttoanuncertainclimatechange.GlobalEnvironmentalChange.Volume19,Issue2,May2009,Pages240–247.doi.org/10.1016/j.gloenvcha.2008.12.003.Hallegatte,S.,Shah,A.,Lempert,R.,Brown,C.andGill,S.(2012).InvestmentDecisionMakingUnderDeepUncertainty:ApplicationtoClimateChange.PolicyResearchWorkingPaper6193.WorldBank.Hallegatte,S.,Lecocq,F.,dePerthuis,C.,2011:Designingclimatechangeadaptationpolicies:Aneconomicframework.PolicyResearchWorkingPaperSeries5568,TheWorldBank.
83
Klein,RJ.T.andPersson,Å(2008).FinancingAdaptationtoClimateChange:IssuesandPriorities.ECPReportNo.8/October2008.EuropeanClimatePlatform(ECP).ISBN978-92-9079-829-7.HMT(2007).GreenBook.AppraisalandEvaluationinCentralGovernmentTreasuryGuidance.London:TSO.HMT(2008).Intergenerationalwealthtransfersandsocialdiscounting:SupplementaryGreenBookguidance.July2008.HerMajesty’sTreasury,LondonUK.IPCC,2012:ManagingtheRisksofExtremeEventsandDisasterstoAdvanceClimateChangeAdaptation.ASpecialReportofWorkingGroupsIandIIoftheIntergovernmentalPanelonClimateChange[Field,C.B.,V.Barros,T.F.Stocker,D.Qin,D.J.Dokken,K.L.Ebi,M.D.Mastrandrea,K.J.Mach,G.-K.Plattner,S.K.Allen,M.Tignor,andP.M.Midgley(eds.)].CambridgeUniversityPress,Cambridge,UK,andNewYork,NY,USA,582pp.IPCC,2014:Summaryforpolicymakers.In:ClimateChange2014:Impacts,Adaptation,andVulnerability.PartA:GlobalandSectoralAspects.ContributionofWorkingGroupIItotheFifthAssessmentReportoftheIntergovernmentalPanelonClimateChange[Field,C.B.,V.R.Barros,D.J.Dokken,K.J.Mach,M.D.Mastrandrea,T.E.Bilir,M.Chatterjee,K.L.Ebi,Y.O.Estrada,R.C.Genova,B.Girma,E.S.Kissel,A.N.Levy,S.MacCracken,P.R.Mastrandrea,andL.L.White(eds.)].CambridgeUniversityPress,Cambridge,UnitedKingdomandNewYork,NY,USA,pp.1-32.LeastDevelopedCountriesExpertGroup(2012a).TheNationalAdaptationPlanProcess:ABriefOverview.UNFCCCsecretariat.Bonn,Germany.December2012.Availableat:http://unfccc.int/files/adaptation/application/pdf/nap_overview.pdfLeastDevelopedCountriesExpertGroup(2012b).NationalAdaptationPlans:Technicalguidelinesforthenationaladaptationplanprocess.UNFCCCsecretariat.Bonn,Germany.December2012.JiaLi,MichaelMullanandJenniferHelgeson(2015).Improvingthepracticeofeconomicanalysisofclimatechangeadaptation.J.BenefitCostAnal.McDonald,R.,Siegel,D.,1986.Thevalueofwaitingtoinvest.QuarterlyJournalofEconomics101,707–723.McGray,H.,A.HammillandR.Bradley(2007),WeatheringtheStorm:OptionsforFramingAdaptationandDevelopment,WorldResourcesInstitute,Washington,D.C.Moser,S.C.&Ekstrom,J.(2010).Aframeworktodiagnosebarrierstoclimatechangeadaptation.ProceedingsoftheNationalAcademyofSciencesoftheUnitedStatesofAmerica,107(51),pp.22026-31.Availableat:http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3009757&tool=pmcentrez&rendertype=abstractOECD(2008),EconomicAspectsofAdaptationtoClimateChange:Costs,BenefitsandPolicyInstruments,OECDPublishing,Paris.OECD,(2012)GreeningDevelopment:EnhancingCapacityforEnvironmentalManagementandGovernance,OECDPublishing.http://dx.doi.org/10.1787/9789264167896-en
84
NicolaRanger,N.,Millner,A.,Dietz,S.,Fankhauser,S.,Lopez,A.andG.Ruta(2010).AdaptationintheUK:adecision-makingprocess.PolicyBriefingNotefortheCommitteeonClimateChangeAdaptationSub-Committee.Ranger,N.HarveyA.&Garbett-Shiels,S.L.(2014)Safeguardingdevelopmentaidagainstclimatechange:evaluatingprogressandidentifyingbestpractice.DevelopmentinPractice,24:4,467-486RavindranathNH.Mitigationandadaptationsynergyinforestsector.MitigAdaptStratGlobChange(2007)12:843–853.DOI10.1007/s11027-007-9102-9.Settele,J.,R.Scholes,R.Betts,S.Bunn,P.Leadley,D.Nepstad,J.T.Overpeck,andM.A.Taboada,2014:Terrestrialandinlandwatersystems.In:ClimateChange2014:Impacts,Adaptation,andVulnerability.PartA:GlobalandSectoralAspects.ContributionofWorkingGroupIItotheFifthAssessmentReportoftheIntergovernmentalPanelonClimateChange[Field,C.B.,V.R.Barros,D.J.Dokken,K.J.Mach,M.D.Mastrandrea,T.E.Bilir,M.Chatterjee,K.L.Ebi,Y.O.Estrada,R.C.Genova,B.Girma,E.S.Kissel,A.N.Levy,S.MacCracken,P.R.Mastrandrea,andL.L.White(eds.)].CambridgeUniversityPress,Cambridge,UnitedKingdomandNewYork,NY,USA,pp.271-359.Stafford-Smith,M.,L.Horrocks,A.Harvey,andC.Hamilto(2011).“RethinkingAdaptationfora4°Cworld.”Phil.Trans.R.Soc.A.369(1934):196–216.doi:10.1098/rsta.2010.0277.Wilby,R.L.andS.Dessai(2010).Robustadaptationtoclimatechange.Weather–July2010,Vol.65,No.7.DOI:10.1002/wea.543.RepublicofRwanda(2012).EconomicDevelopmentAndPovertyReductionStrategy2013–2018.UNDP/UNEP(2011).MainstreamingClimateChangeAdaptationintoDevelopmentPlanning:AGuideforPractitioners.UNDP-UNEPPoverty-EnvironmentInitiative.Watkiss,P.andA.Hunt,2011:MethodfortheUKAdaptationEconomicAssessment(EconomicsofClimateResilience).FinalReporttoDefra.May2011.Deliverable2.2.1Watkissetal.,2013.Ethiopia’sClimateResilientStrategyforAgriculture.TechnicalreporttotheFederalRepublicofEthiopia.Watkissetal.(2014).EarlyValue-for-MoneyAdaptation:DeliveringVfMAdaptationusingIterativeFrameworksandLow-RegretOptions,DFID,London.Watkiss,P.,Hunt,A.,Blyth,W.andDyszynski,J(2014).Theuseofneweconomicdecisionsupporttoolsforadaptationassessment:Areviewofmethodsandapplications,towardsguidanceonapplicability.ClimaticChange.DOI:10.1007/s10584-014-1250-9Watkiss,P.,Benzie,M.,andKlein,R(2015).Thecomplementarityandcomparabilityofmitigationandadaptation.SEIworkingpaper.SubmittedtoWIRESclimatechange.Weitzman,M.L.OnModelingandInterpretingtheEconomicsofCatastrophicClimateChange,TheReviewofEconomicsandStatistics,2009,91(1):1-19.WorldBank.2006.CleanEnergyandDevelopment:TowardsanInvestmentFramework.ESSD-VP/I-VP.April5,2006.Washington,DC:TheWorldBank.
85
WorldBank(2007).HandbookonEconomicanalysisofInvestmentoperations.PedroBelli,JockAnderson,HowardBarnum,JohnDixon,Jee-PengTan.JuzhongZhuang,ZhihongLiang,TunLin,andFranklinDeGuzman(2007).TheoryandPracticeintheChoiceofSocialDiscountRateforCost-benefitAnalysis:ASurvey.ERDWorkingPaperNo.94CostsandbenefitsofadaptationinAfricaAfDB(2011)ThecostofadaptationtoclimatechangeinAfrica.Tunis,TN:AfricanDevelopmentBank(AfDB).Agrawala,S.etal.(2011).“AdaptingtoClimateChange:Costs,Benefits,andModellingApproaches”,InternationalReviewofEnvironmentalandResourceEconomics,Volume5(3),http://dx.doi.org/10.1561/101.00000043.AIACC(2006).EstimatingandComparingCostsandBenefitsofAdaptationProjects:CaseStudiesinSouthAfricaandTheGambia.AFinalReportSubmittedtoAssessmentsofImpactsandAdaptationstoClimateChange(AIACC),JabavuCNkomoandBernardGomez,ProjectNo.AF47.v.PublishedbyTheInternationalSTARTSecretariat,Washington,DCUSA.Branca,G.,L.LipperandA.Sorrentino(2012),“Benefit-costsanalysisofclimate-relatedagriculturalinvestmentsinAfrica:acasestudyˮ,ItalianAssociationofAgriculturalandAppliedEconomics,CongressPapers,2012FirstCongress,June4-5,2012,Trento,Italy.Branca,G.etal.(2011),“Climate-SmartAgriculture:ASynthesisofEmpiricalEvidenceofFoodSecurityandMitigationBenefitsfromImprovedCroplandManagement”,MitigationOfClimateChangeInAgricultureSeries,No.3,FAO,Rome.SallyBrown,AbiyS.KebedeandRobertJ.Nicholls(2009).Sea-LevelRiseandImpactsinAfrica,2000to2100.StudyCommissionedaspartofUNEP‘AdaptCost’study.November2009.AntonCartwright,JamesBlignaut,MartinDeWit,KarenGoldberg,MylesMander,SeanO'DonoghueandDebraRoberts(2013).Economicsofclimatechangeadaptationatthelocalscaleunderconditionsofuncertaintyandresourceconstraints:thecaseofDurban,SouthAfrica.EnvironmentandUrbanization201325:139.DOI:10.1177/0956247813477814Chambwera,M.,G.Heal,C.Dubeux,S.Hallegatte,L.Leclerc,A.Markandya,B.A.McCarl,R.Mechler,andJ.E.Neumann]:Economicsofadaptation.In:ClimateChange2014:Impacts,Adaptation,andVulnerability.PartA:GlobalandSectoralAspects.ContributionofWorkingGroupIItotheFifthAssessmentReportoftheIntergovernmentalPanelonClimateChange[Field,C.B.,V.R.Barros,D.J.Dokken,K.J.Mach,M.D.Mastrandrea,T.E.Bilir,M.Chatterjee,K.L.Ebi,Y.O.Estrada,R.C.Genova,B.Girma,E.S.Kissel,A.N.Levy,S.MacCracken,P.R.Mastrandrea,andL.L.White(eds.)].CambridgeUniversityPress,Cambridge,UnitedKingdomandNewYork,NY,USA,pp.945-977.Doczi,J.,andRoss,I.(2014).TheeconomicsofclimatechangeadaptationinAfrica'swatersector.Areviewandawayforward.London,UK:IIEDandtheGranthamInstituteforClimateChange.Downing,T.andChambwera,M.,CabotVenton,C.,Dyszynski,J.,Crawford,V.,2011.Planningandcostingagriculture’sadaptationtoclimatechange:PolicyPerspectives.InternationalInstituteforEnvironmentandDevelopment(IIED),London,UK.
86
ECA(2009).ShapingClimate-resilientDevelopmentaframeworkfordecision-making.AreportoftheeconomicsofclimateAdaptationworkinggroup.EconomicsofClimateAdaptation.ECONADAPT(2015).TheCostsandBenefitsofAdaptation.ResultsfromtheECONADAPTProject,ECONADAPTconsortium,availableathttp://econadapt.eu/.StephaneHallegatte,ColinGreen,RobertJ.NichollsandJanCorfee-Morlot(2013).Futurefloodlossesinmajorcoastalcities.NatureClimateChange3,802–806(2013)doi:10.1038/nclimate1979Kurukulasuriya,P.,andR.Mendelsohn.2007.CropSelection:AdaptingtoclimatechangeinAfrica,PolicyResearchWorkingPaperSeries,WorldBank.Kurukulasuriya,P.andR.Mendelsohn.2008.CropSwitchingasanAdaptationStrategytoClimateChange.AfricanJournalAgricultureandResourceEconomics2:105-125.Kurukulasuriya,P.,N.KalaandR.Mendelsohn.2011.AdaptationandClimateChangeImpacts:AStructuralRicardianModelofIrrigationandFarmIncomeinAfrica.ClimateChangeEconomics2(2):149-174.Lunduka,R.W.(2013).MultipleStakeholders’EconomicAnalysisinClimateChangeAdaptation–CaseStudyofLakeChilwaCatchmentinMalawi.InternationalInstituteforEnvironmentandDevelopment(IIED),London,UK.MatiyaG.,Lunduka,R.,andSikwese,M.2011.“Costingclimatechangeadaptationinagriculture:Acasestudyofsmall-scalemaizeproductioninMalawi.”ReporttoDFID.http://weadapt.org/knowledge-base/economics-of-adaptation/planning-and-costing-agricultures-adaptation-in-malawiMuller,M.(2007),“AdaptingtoClimateChange:WaterManagementforUrbanResilience”,EnvironmentandUrbanization19(1),pp.99-112.OECD(2008),EconomicAspectsofAdaptationtoClimateChange:Costs,BenefitsandPolicyInstruments,OECDPublishing,Paris,http://dx.doi.org/10.1787/9789264046214-en.UNDP(2011).AssessmentofInvestmentandFinancialFlowstoAddressClimateChange(CapacityDevelopmentforPolicyMakerstoAddressClimateChange).Countrysummaries.Availableat:http://www.undpcc.org/en/financial-analysis/results.WorldBank(2010).TheCoststoDevelopingCountriesofAdaptingtoClimateChange:NewMethodsandEstimates.TheGlobalReportoftheEconomicsofAdaptationtoClimateChangeStudy.SynthesisReport.WorldBank,Washington.WorldBank.(2010).Mozambique-Economicsofadaptationtoclimatechange.Vol.1ofMozambique-Economicsofadaptationtoclimatechange.Washington,DC:WorldBankWorldBank.(2010).Mainreport.Vol.1ofGhana-EconomicsofAdaptationtoClimateChange(EACC).WashingtonD.C.:TheWorldbank.WorldBank(2010).Ethiopia-Economicsofadaptationtoclimatechange.Washington,DC:WorldBank.
87
WorldBank(2011).NaturalHazards,UnNaturalDisasters,TheEconomicsofEffectivePrevention.WorldBank,Washington.WorldBank(2013)."Weather,ClimateandWaterHazardsandClimateResilience:EffectivePreparednessthroughNationalMeteorologicalandHydrologicalServices.UNFCCC(2009).Potentialcostsandbenefitsofadaptationoptions:Areviewofexistingliterature.TechnicalPaper.Markandya,A.andWatkiss,P.CDCeCce/mTPb/e2r020090/29.UNFCCC(2010).SynthesisreportontheNationalEconomic,EnvironmentandDevelopmentStudy(NEEDS)forClimateChangeProject.CapitalinvestmentsBu,Y.,2006.Fixedcapitalstockdepreciationindevelopingcountries:Someevidencefromfirmleveldata.JournalofDevelopmentStudies,42,pp.881–901.Davoodi,H.&Tanzi,V.,1997.Corruption,PublicInvestment,andGrowth.IMFWorkingPaperWP/97/139(Washington:InternationalMonetaryFund).Easterly,W.&Rebelo,S.,1993.Fiscalpolicyandeconomicgrowth:Anempiricalinvestigation.JournalofMonetaryEconomics,32,pp.417–458.Nordhaus,W.D.&Sztorc,P.,2013.DICE2013R:IntroductionandUser’sManual,Schuendlen,M.,2013.Appreciatingdepreciation:physicalcapitaldepreciationinadevelopingcountry.EmpiricalEconomics,44,pp.1277–1290.Udry,C.etal.,2006.ThereturntocapitalinGhana.InAmericanEconomicReview.pp.388–393.QuantitativeInvestmentsandLock-inBarr,R.,Fankhauser,S.,&Hamilton,K.(2010).Adaptationinvestments:aresourceallocationframework.MitigationandAdaptationStrategiesforGlobalChange,15(8),843–858.doi:10.1007/s11027-010-9242-1Barro,R.J.,&Sala-i-Martin,X.(2004).EconomicGrowth(2nded.).MITPress.FoodandAgricultureOrganizationoftheUN.(2014).FAOAquaStatistics.RetrievedFebruary16,2015,fromhttp://www.fao.org/nr/water/aquastat/data/query/index.html?lang=enIMF.(2014).WorldEconomicOutlookDatabase,October2014.Ranger,N.,Harvey,A.,&Garbett-Shiels,S.-L.(2014).Safeguardingdevelopmentaidagainstclimatechange:evaluatingprogressandidentifyingbestpractice.DevelopmentinPractice,24(4),467–486.TheProgrammeforInfrastructureDevelopmentinAfrica.(2010).AfricaEnergySector:Outlook2040.TradingEconomics.(2014).CreditRatings.RetrievedFebruary16,2015,fromhttp://www.tradingeconomics.com/country-list/rating
88
U.S.EnergyInformationAdministration(EIA).(2014).InternationalEnergyStatistics.RetrievedFebruary16,2015,fromhttp://www.eia.gov/cfapps/ipdbproject/IEDIndex3.cfmUNDESA.(2014).CityPopulationForecasts.RetrievedFebruary16,2015,fromhttp://esa.un.org/unpd/wup/Highlights/WUP2014-Highlights.pdfUSDepartmentofCommerce.(2014).BEADepreciationEstimates.Retrievedfromhttp://www.bea.gov/national/pdf/BEA_depreciation_rates.pdfUSDepartmentoftheTreasury.(2012).HowToDepreciateProperty.Retrievedfromhttp://www.irs.gov/pub/irs-pdf/p946.pdfWorldBank.(2013).ChangingWealthofNations.RetrievedFebruary16,2015,fromhttp://data.worldbank.org/data-catalog/wealth-of-nationsWorldBank.(2014a).Health,NutritionandPopulationStatistics.RetrievedFebruary16,2015,fromhttp://databank.worldbank.org/Data/Views/VariableSelection/SelectVariables.aspx?source=HealthNutritionandPopulationStatistics:Populationestimatesandprojections#WorldBank.(2014b).TheAtlasofSocialProtection:IndicatorsofResilienceandEquity(ASPIRE).RetrievedFebruary16,2015,fromhttp://databank.worldbank.org/data/views/variableselection/selectvariables.aspx?source=the-atlas-of-social-protection:-indicators-of-resilience-and-equity-(aspire)WorldBank.(2014c).WorldDevelopmentIndicators.RetrievedFebruary16,2015,fromhttp://databank.worldbank.org/data/views/variableSelection/selectvariables.aspx?source=world-development-indicators#WorldBank.(2014d).WorldDevelopmentIndicators2014.Retrievedfromhttp://data.worldbank.org/data-catalog/world-development-indicatorsWorldBank.(2014e).WorldwideGovernanceIndicators.WorldEnergyCouncil.(2013).WorldEnergyResources,468.Yepes,T.,Yepes,T.,Pierce,J.,Pierce,J.,Foster,V.,&Foster,V.(2008).MakingSenseofAfrica’sInfrastructureEndowment:ABenchmarkingApproach.AfricaInfrastructureCountryDiagnostic(Washington:WorldBank).Yohe,G.,Malone,E.,Brenkert,A.,Schlesinger,M.,Meij,H.,&Xing,X.(2006).Globaldistributionsofvulnerabilitytoclimatechange.TheIntegratedAssessmentJournal,6,35–44.DecisionmakingunderuncertaintyAIACC(AssessmentsofImpactsandAdaptationstoClimateChange)(2006).EstimatingandComparingCostsandBenefitsofAdaptationProjects:CaseStudiesinSouthAfricaandTheGambia.AFinalReportSubmittedtoAIACC,theInternationalSTARTSecretariat,Washington,DC.Boyd,R.,S.WadeandH.Walton(2006),ClimateChangeImpactsandAdaptation:Cross-RegionalResearchProject(E),Defra,UK.
89
DeBruin,K.,R.B.Dellink,A.Ruijs,L.Bolwidt,A.VanBuuren,J.Graveland,R.S.,DeGroot,P.J.Kuikman,S.Reinhard,R.P.Roetter,V.C.Tassone,A.Verhagen,andE.C.VanIerland(2009).‘AdaptingtoclimatechangeintheNetherlands:Aninventoryofclimateadaptationoptionsandrankingofalternatives’,ClimaticChange95(1–2),2009,23–45.Cartwright,A.,Blignaut,J.,DeWit,M.,Goldberg,K.,Mander,M.,O'Donoghue,S.,andD.Roberts(2013).Economicsofclimatechangeadaptationatthelocalscaleunderconditionsofuncertaintyandresourceconstraints:thecaseofDurban,SouthAfrica.EnvironmentandUrbanization201325:139.DOI:10.1177/0956247813477814CroweK.A.andW.H.Parker(2008)Usingportfoliotheorytoguidereforestationandrestorationunderclimatechangescenarios.ClimaticChange89:355-370.Darch,G.,Arkell,B.andTradewell,J.2011.WaterresourceplanningunderclimateuncertaintyinLondon.AtkinsReport(Reference5103993/73/DG/035)fortheAdaptationSub-CommitteeandThamesWater.Atkins,Epsom.Deltacommissie(2008),Workingtogetherwithwater:Alivinglandbuildsforitsfuture,Deltacommissie,theNetherlands.DeltaProgramme,2011.WorkingontheDelta.The2011DeltaProgramme.InvestinginaSafeandAttractiveNetherlands,NowandintheFuture.http://www.deltacommissaris.nl/english/Images/Deltaprogramma_ENG1_tcm310-286802.pdf.DeltaProgramme,2014PromisingSolutionsforTaskingandAmbitions.DeltaProgramme2014:Decisions.http://www.deltacommissaris.nl/english/Images/Delta%20Programme%202014_English_tcm310-345435.pdfDessaiSandM.Hulme(2007)Assessingtherobustnessofadaptationdecisionstoclimatechangeuncertainties:AcasestudyonwaterresourcesmanagementintheEastofEngland,GlobalEnvironmentalChange,17,pp.59-72.Dobes,L(2010).NotesonApplyingRealOptionstoClimateChangeAdaptationMeasures,withexamplesfromVietnam.EnvironmentalEconomicsResearch.November2010.ResearchReportNo.75.ISSN1835-9728EA(2009).TE2100PlanTechnicalReport.AppendixH.AppraisalinTE2100.EnvironmentAgencyEA(2011).TE2100StrategicOutlineProgramme(EnvironmentAgency,2011)ECONADAPT(2015).TheCostsandBenefitsofAdaptation.ResultsfromtheECONADAPTProject,ECONADAPTconsortium,availableathttp://econadapt.eu/.Gersonius,B.,Ashley,R.Pathirana,A.,andZevenbergen,C.(2013).Climatechangeuncertainty:buildingflexibilityintowaterandfloodriskinfrastructure.ClimaticChange,Volume116,Issue2,pp411-423.10.1007/s10584-012-0494-5
90
Groves,D.G.Fischbach,J.R.Bloom,E.,Knopman,D.Keefe,R.(2013).AdaptingtoaChangingColoradoRiver.MakingFutureWaterDeliveriesMoreReliableThroughRobustManagementStrategies.ISBN/EAN:9780833081797.Groves,D.G.andSharon,C.(2013).PlanningTooltoSupportPlanningtheFutureofCoastalLouisiana.JournalofCoastalResearch:SpecialIssue67-Louisianaʹs2012CoastalMasterPlanTechnicalAnalysis:147-161.2013.Haasnoot,M.,J.H.Kwakkel,W.E.WalkerandJ.T.Maat(2013)DynamicAdaptivePolicyPathways:AMethodforCraftingRobustDecisionsforaDeeplyUncertainWorld.GlobalEnvironmentalChange23(2),485–498.Hallegatte,S.,Shah,A.,Lempert,R.,Brown,C.andGill,S.(2012).InvestmentDecisionMakingUnderDeepUncertainty:ApplicationtoClimateChange.PolicyResearchWorkingPaper6193.WorldBank.Hunt,A.(2009)EconomicAspectsofClimateChangeImpactsandAdaptationintheUK.PhDThesis.UniversityofBath.IFC(2011).ClimateRiskandBusiness:Ports.TerminalMarítimoMuelleselBosqueCartagena,Colombia.PublishedbytheInternationalFinanceCorporation2011.Jeuland,MandWhittington,D(2013).WaterResourcesPlanningunderClimateChange:A“RealOptions”ApplicationtoInvestmentPlanningintheBlueNile.Environment-for-Development.EfDDP13-05.Kontogianni,A.,C.H.Tourkolias,D.DamigosandM.Skourtos(2013).Assessingsea-level-risecostsandadaptationbenefitsunderuncertaintyinGreece.EnvironmentalScience&Policy.Linquiti,P.andN.Vonortas(2012).Thevalueofflexibilityinadaptingtoclimatechange:arealoptionsanalysisofinvestmentsincoastaldefense.ClimateChangeEconomics03(02):1250008.LempertR.J.andGroves,D.G(2010).IdentifyingandevaluatingrobustadaptivepolicyresponsestoclimatechangeforwatermanagementagenciesintheAmericanwest.TechnologicalForecasting&SocialChange,77,960-974.Lempert,R.J.Kalra,N.Peyraud,S.Mao,Z.Sinh-Bach-Tan,S.Cira,D.andLotsch,A.(2013).EnsuringRobustFloodRiskManagementinHoChiMinhCity.PolicyResearchWorkingPaperWPS6465.WorldBank.HypatiaNassopoulosPatriceDumasStéphaneHallegatte(2013).AdaptationtoanUncertainClimateChange:CostBenefitAnalysisandRobustDecisionMakingforDamDimensioning.ClimaticChange(2012)114:497–508.DOI10.1007/s10584-012-0423-7NicolaRanger,N.,Millner,A.,Dietz,S.,Fankhauser,S.,Lopez,A.andG.Ruta(2010).AdaptationintheUK:adecision-makingprocess.PolicyBriefingNotefortheCommitteeonClimateChangeAdaptationSub-Committee.Reeder,TandRanger,N(2011).“Howdoyouadaptinanuncertainworld?LessonsfromtheThamesEstuary2100project.”WorldResourcesReport,Washington.
91
Scandizzo,P.L.,(2011).ClimateChangeAdaptationandRealOptionEvaluation.CEISWorkingPaper232.Tainio,A.,HeikkinenR.K.,Helio¨la,J.,¨Hunt,A.,Watkiss,P.,Fronzek,S.,Leikola,N.,Lotjonen,S.,Mashkina,O.andT.R.Carter(2014)ConservationofgrasslandbutterfliesinFinlandunderachangingclimate.RegionalEnvironmentalChange,UBA(2012):KostenundNutzenvonAnpassungsmaßnahmenandenKlimawandel:Analysevon28AnpassungsmaßnahmeinDeutschland.(Costsandbenefitsofclimateadaptationmeasures.Analysisof28adaptationmeasuresinGermany).GermanFederalEnvironmentalAgency(UBA),ClimateChangeNr.10/2012,Dessau.VanderPol,T.D.,VanIerland,E.C.andWeikard,H.-P.(2013)OptimalDikeInvestmentsunderUncertaintyandLearningaboutIncreasingWaterLevels.JournalofFloodRiskManagement(underreview)VanIerlandEC,deBruinK,DellinkRB,RuijsA(eds)(2007).Aqualitativeassessmentofclimateadaptationoptionsandsomeestimatesofadaptationcosts.ReportsontheRouteplannerprojects3,4and5(Routeplannerdeelprojecten3,4en5),WageningenUR.Availableatwww.enr.wur.nl/UK/Routeplanner+ReportWatkiss,P.,Hunt,A.,Blyth,W.andDyszynski,J(2014).Theuseofneweconomicdecisionsupporttoolsforadaptationassessment:Areviewofmethodsandapplications,towardsguidanceonapplicability.ClimaticChange.DOI:10.1007/s10584-014-1250-9WorldBank(2012).Hallegatte,S.,Shah,A.,Lempert,R.,Brown,C.andGill,S..InvestmentDecisionMakingUnderDeepUncertainty:ApplicationtoClimateChange.PolicyResearchWorkingPaper6193.WorldBank.BarrierstoAdaptationAakre,StineandDirkT.G.Rübbelke,2010.ObjectivesofPublicEconomicPolicyandtheAdaptationtoClimateChange.JournalofEnvironmentalPlanningandManagement,53(6):pp.767-791.Adger,W.N.,J.Barnett,K.Brown,N.A.Marshall,andK.O’Brien,2012:Culturaldimensionsofclimatechangeimpactsandadaptation.NatureClimateChange,3,112-117.Adger,W.N.,T.Quinn,I.Lorenzoni,C.Murphy,andJ.Sweeney,2013:Changingsocialcontractsinclimate-changeadaptation.NatureClimateChange,3(4),330-333.Ainslie,G.,1975:Speciousreward:abehavioraltheoryofimpulsivenessandimpulsecontrol.PsychologicalBulletin,82(4),463-496.AmericanPsychologicalAssociation,2011:PsychologyandGlobalClimateChange:AddressingaMulitfacetedPhenomenonandSetofChallenges,2011,Washington:AmericanPsychologicalAssociation.Artur,L.andD.Hilhorst,2012:EverydayrealitiesofclimatechangeadaptationinMozambique.GlobalEnvironmentalChange,22(2),529-536.
92
Biesbroek,G.R.,J.Klostermann,C.Termeer,andP.Kabat,2013a:Onthenatureofbarrierstoclimatechangeadaptation.RegionalEnvironmentalChange,13(5),1119-1129.Burby,R.J.,A.B.Cigler,S.P.French,E.J.Kaiser,J.Kartez,D.Roenigk,D.Weist,andD.Whittington,1991:SharingEnvironmentalRisks:HowtoControlGovernments’LossesinNaturalDisasters.WestviewPress,Boulder,CO,USA,280pp.Carter,T.R.,Parry,M.L.,Harasawa,H.,Nishioka,S.,1994:IPCCTechnicalGuidelinesforAssessingClimateChangeImpactsandAdaptations.DepartmentofGeography,UniversityCollege,London.CashDW,AdgerWN,BerkesF,GardenP,LebelL,OlssonP,PritchardL,YoungO,2006:Scaleandcross-scaledynamics:governanceandinformationinamulti-levelworld.EcologyandSociety11(2):8.Chambwera,M.,G.Heal,C.Dubeux,S.Hallegatte,L.Leclerc,A.Markandya,B.A.McCarl,R.Mechler,andJ.E.Neumann,2014:Economicsofadaptation.In:ClimateChange2014:Impacts,Adaptation,andVulnerability.PartA:GlobalandSectoralAspects.ContributionofWorkingGroupIItotheFifthAssessmentReportoftheIntergovernmentalPanelonClimateChange[Field,C.B.,V.R.Barros,D.J.Dokken,K.J.Mach,M.D.Mastrandrea,T.E.Bilir,M.Chatterjee,K.L.Ebi,Y.O.Estrada,R.C.Genova,B.Girma,E.S.Kissel,A.N.Levy,S.MacCracken,P.R.Mastrandrea,andL.L.White(eds.)].CambridgeUniversityPress,Cambridge,UnitedKingdomandNewYork,NY,USA,pp.945-977.Cimato,F.andM.Mullan,2010:AdaptingtoClimateChange:AnalysingtheRoleofGovernment.DEFRAEvidenceandAnalysisSeriesPaper1,DepartmentforEnvironment,FoodandRuralAffairs(DEFRA),London,UK,79pp.Clar,C.,A.PrutschandR.Steurer2011:Barriersandguidelinesinadaptationpolicymaking:Takingstock,analysingcongruenceandprovidingguidance.Availableonlinefrom:http://www.adaptgov.com/wp-content/uploads/2012/03/Clar-Barriers-guidelinesinadaptation-policy-A86-Tscience.pdfClar,C.,A.Prutsch,andR.Steurer,2013:Barriersandguidelinesforpublicpoliciesonclimatechangeadaptation:amissedopportunityofscientificknowledgebrokerage.NaturalResourcesForum,37(1),1-18.Craig,R.K.,2010:“Stationarityisdead”–longlivetransformation:fiveprinciplesforclimatechangeadaptationlaw.HarvardEnvironmentalLawReview,34,9-73.DawnayE.,H.Shah,2005:Behaviouraleconomics:sevenprinciplesforpolicymakers.NewEconomicsFoundationworkingpaper.Dow,K.,F.Berkhout,andB.L.Preston,2013a:Limitstoadaptation:ariskapproach.CurrentOpinioninEnvironmentalSustainability,5(3-4),384-391.Dow,K.,F.Berkhout,B.L.Preston,R.J.T.Klein,G.Midgley,andR.Shaw,2013b:Limitstoadaptation.NatureClimateChange,3,305-307.EC,2013:GuidelinesonDevelopingAdaptationStrategies.Brussels,16.4.2013,Eisenack,K.andR.Stecker;2012:Aframeworkforanalyzingclimatechangeadaptationsasactions.MitigationandAdaptationStrategiesforGlobalChange,17,243-260.
93
FAO,2013:Climate-SmartAgricultureSourcebook.FoodandAgricultureOrganizationoftheUnitedNations(FAO),Rome,Italy,557pp.Folke,C.,S.Carpenter,T.Elmqvist,L.Gunderson,C.S.Holling,B.Walker,J.Bengtsson,F.Berkes,J.Colding,K.Danell,M.Falkenmark,L.Gordon,R.Kasperson,N.Kautsky,A.Kinzig,S.Levin,K.-G.Mäler,F.Moberg,L.Ohlsson,P.Olsson,E.Ostrom,W.Reid,J.Rockström,H.Savenije,andU.Svedin.2002:Resilienceandsustainabledevelopment:buildingadaptivecapacityinaworldoftransformations.InternationalCouncilforScience,Paris,France.Folke,C.,T.Hahn,P.Olsson,andJ.Norberg,2005:Adaptivegovernanceofsocial-ecologicalsystems.AnnualReviewofEnvironmentandResources30:441-473.Folke,C.,L.Pritchard,F.Berkes,J.Colding,andU.Svedin.1998.Theproblemoffitbetweenecosystemsandinstitutions.InternationalHumanDimensionsProgrammeonGlobalEnvironmentalChange,Bonn,Germany.FankhauserS.,SmithJ.B.,TolR.S.J.,1999:Weatheringclimatechange:somesimplerulestoguideadaptationdecisions.EcologicalEconomics30,67-78.FrontierEconomics,2013:Theeconomicsofclimateresilience.SynthesisReport.Goulden,M.,D.Conway,andA.Persechino,2009:AdaptationtoclimatechangeininternationalriverbasinsinAfrica:areview/AdaptationauchangementclimatiquedanslesbassinsfluviauxinternationauxenAfrique:unerevue.HydrologicalSciencesJournal,54(5),805-828.Hall,J.W.2007:Probabilisticclimatescenariosmaymisrepresentuncertaintyandleadtobadadaptationdecisions.HydrologicalProcesses,21(8),1127-1129.Hallegatte,S.,Lecocq,F.,dePerthuis,C.,2011.Designingclimatechangeadaptationpolicies:Aneconomicframework.PolicyResearchWorkingPaperSeries5568,TheWorldBank.Herrfahrdt-Pähle,E.,2013:Integratedandadaptivegovernanceofwaterresources:thecaseofSouthAfrica.RegionalEnvironmentalChange,13(3),551-561.Hunt,A.,Watkiss,P.,2011.Climatechangeimpactsandadaptationincities:areviewoftheliterature.ClimaticChange104,13-49.Huntjens,P.,L.Lebel,C.Pahl-Wostl,J.Camkin,R,Schulze,andN.Kranz,2012:Institutionaldesignpropositionsforthegovernanceofadaptationtoclimatechangeinthewatersector.GlobalEnvironmentalChange,22(1),67-81.IPCCTAR,2001a.ClimateChange2001:Impacts,AdaptationandVulnerability.IPCCThirdAssessmentReport,CambridgeUniversityPress.IPCCTAR,2001b.ClimateChange2001:TheScientificBasis.IPCC.IPCCThirdAssessmentReport,CambridgeUniversityPressIPCC,2007a:ClimateChange2007:ThePhysicalScienceBasis.ContributionofWorkingGroup1totheFourthAssessmentReportoftheIntergovernmentalPanelonClimateChange[Solomon,S;D.Qin;M.Manning;Z.Chen;M.Marquis;K.B.Averyt;M.Tignor;andH.L.Miller,Eds.],CambridgeUniversityPress,Cambridge,UnitedKingdomandNewYork,NY,USA.
94
IPCC,2007b:ClimateChange2007:Impacts,AdaptationandVulnerability.ContributionofWorkingGroupIItotheFourthAssessmentReportoftheIntergovernmentalPanelonClimateChange[Parry,M.,O.Canziani,J.Palutikof,andP.vanderLinden(eds.)].CambridgeUniversityPress,Cambridge,UKandNewYork,NY,USA,976pp.IPCC,2012:ManagingtheRisksofExtremeEventsandDisasterstoAdvanceClimateChangeAdaptation.ASpecialReportofWorkingGroupsIandIIoftheIntergovernmentalPanelonClimateChange[Field,C.B.,V.Barros,T.F.Stocker,D.Qin,D.J.Dokken,K.L.Ebi,M.D.Mastrandrea,K.J.Mach,G.-K.Plattner,S.K.Allen,M.Tignor,andP.M.Midgley(eds.)].CambridgeUniversityPress,Cambridge,UKandNewYork,NY,USA,582pp.Islam,M.,S.Sallu,K.Hubacek,andJ.Paavola,2014:LimitsandbarrierstoadaptationtoclimatevariabilityandchangeinBangladeshicoastalfishingcommunities.MarinePolicy,43,208-216.JonesB.D.,2002:Boundedrationalityandpublicpolicy:HerbertA.Simonandthedecisionalfoundationofcollectivechoice.PolicySciences35:269-284.JonesB.D.,2010:BoundedrationalityAnnu.Rev.Polit.Sci.1999.2:297–321.Jones,L.andE.Boyd,2011:Exploringsocialbarrierstoadaptation:insightsfromWesternNepal.GlobalEnvironmentalChange,21(4),1262-1274.Klein,R.J.T.,G.F.Midgley,B.L.Preston,M.Alam,F.G.H.Berkhout,K.Dow,andM.R.Shaw,2014:Adaptationopportunities,constraints,andlimits.In:ClimateChange2014:Impacts,Adaptation,andVulnerability.PartA:GlobalandSectoralvAspects.ContributionofWorkingGroupIItotheFifthAssessmentReportoftheIntergovernmentalPanelonClimateChange.Kuch,P.J.,Gigli,S.,2007.Economicapproachestoadaptationandtheirroleinprojectprioritisationandappraisal.EditedbyDeutscheGesellschaftfürTechnischeZusammenarbeit(GTZ).W.B.Druckerei,Hochheim.Kuruppu,N.andD.Liverman,2011:Mentalpreparationforclimateadaptation:theroleofcognitionandcultureinenhancingadaptivecapacityofwatermanagementinKirabati.GlobalEnvironmentalChange,21(2),657-669.Kwakkel,J.H.;Walker,W.E.;Marchau,V.A.W.J.Classifyingandcommunicatinguncertaintiesinmodel-basedpolicyanalysis.Int.J.Technol.PolicyManage.2010,10,299–315.Laffont,J.J.,1995:Regulation,moralhazardandinsuranceofenvironmentalrisks.JournalofPublicEconomics,58(3),319-336.Lamhauge,N.,Lanzi,E.,Agrawala,S.,2012:Monitoringandevaluationforadaptation:Lessonsfromdevelopmentco-operationagencies.OECDEnvironmentWorkingPapers38,OECDPublishing.LeeS.andS.Thornsbury,2010:Theeffectofmarketstructureonadaptationtoclimatechangeinagriculture.ContributedpaperattheIATRCPublicTradePolicyResearchandAnalysisSymposium‘ClimateChangeinWorldAgriculture:Mitigation,Adaptation,TradeandFoodSecurity’UniversitätHohenheim,Stuttgart,Germany,June27-29,LehmannP.,M.Brenck,O.Gebhardt,S.Schaller,andE.Süßbauer,2012:Understandingbarriersandopportunitiesforadaptationplanningincities.UFZDiscussionPapers,No.9/2012.
95
Lempert,R.J.,Popper,S.,Bankes,S.ShapingtheNextOneHundredYears:NewMethodsforQuantitative,LongTermPolicyAnalysis;ReportMR-1626-RPC;RAND:SantaMonica,CA,USA,2003.Lesnikowski,A.C.,J.D.Ford,L.Berrang-Ford,M.Barrera,P.Berry,J.Henderson,andS.J.Heymann,2013:National-levelfactorsaffectingplanned,publicadaptationtohealthimpactsofclimatechange.GlobalEnvironmentalChange,23(5),1153-1163.MaddisonD.,2007:ThePerceptionofandAdaptationtoClimateChangeinAfrica.PolicyResearchWorkingPaper4308,DevelopmentResearchGroup,SustainableRuralandUrbanDevelopmentTeam,TheWorldBank.Mendelsohn,R.,2000:Efficientadaptationtoclimatechange.ClimaticChange,45,583-600.MoserS,DillingL(eds),2007:Creatingaclimateforchange:communicatingclimatechangeandfacilitatingsocialchange.CambridgeUniversityPress,Cambridge,549pp.MoserSC,DillingL2004:Makingclimatehot.Communicatingtheurgencyandchallengeofglobalclimatechange.Environment46(10):32–46.Moser,S.C.andJ.A.Ekstrom,2010:Aframeworktodiagnosebarrierstoclimatechangeadaptation.ProceedingsoftheNationalAcademyofSciencesoftheUnitedStatesofAmerica,107(51),22026-22031.Mustelin,J.,R.Klein,B.Assaid,T.Sitari,M.Khamis,A.Mzee,andT.Haji,2010:Understandingcurrentandfuturevulnerabilityincoastalsettings:communityperceptionsandpreferencesforadaptationinZanzibar,Tanzania.Population&Environment,31(5),371-398.O’BrienKL,EriksenS,SygnaL,NaessLO,2006:Questioningcomplacency:climatechangeimpacts,vulnerability,andadaptationinNorway.Ambio35(2):50–56.OberlackC.andK.Eisenack,2012:Overcomingbarrierstourbanadaptationthroughinternationalcooperation?ModesanddesignpropertiesundertheUNFCCC.TheConstitutionalEconomicsNetworkWorkingPapers,No.03-2012Oberlack,C,Neumärker,Bernhard,2011:Economics,institutionsandadaptationtoclimateChange.TheConstitutionalEconomicsNetworkWorkingPapers,No.04-2011.Osberghaus,D.,A.Dannenberg,T.Mennel,andB.Sturm,2010a:Theroleofthegovernmentinadaptationtoclimatechange.EnvironmentandPlanningC:GovernmentandPolicy,28(5),834-850.Osberghaus,D.,E.Finkerl,andM.Pohl,2010b:IndividualAdaptationtoClimateChange:TheRoleofInformationandPerceivedRisk.ZEWDiscussionPaperNo.10-061,ZentrumfürEuropäischeWirtschaftsforschung(ZEW)GmbH,CentreforEuropeanEconomicResearch,Mannheim,Germany,31pp.Park,S.E.,N.A.Marshall,E.Jakku,A.M.Dowd,S.M.Howden,andA.Fleming,2012:Informingadaptationresponsestoclimatechangethroughtheoriesoftransformation.GlobalEnvironmentalChange,22(1),115-126.PatonD,MillarM,JohnstonD,2001:Communityresiliencetovolcanichazardconsequences.NaturalHazards24:157–169.
96
Podsakoff,P.M.,S.B.MacKenzie,R.H.Moorman,andR.Fetter,1990:Transformationalleaderbehaviorsandtheireffectsonfollowers’trustinleader,satisfaction,andorganizationalcitizenshipbehaviors.LeadershipQuarterly,1(2),107-142.Rademacher-Schulz,C.&Mahama,E.S.,2012:"Wheretherainfalls"project.Casestudy:Ghana.ResultsfromNadowlidistrict,UpperWestregion.ReportNo.3.Bonn:TheUNUInstituteforEnvironmentandHumanSecurity.Samuelson,P.A.,1954:Thepuretheoryofpublicexpenditure.ReviewofEconomicsandStatistics,36(4),387-389.Schilling,J.,K.P.Freier,E.Hertig,andJ.Scheffran,2012:Climatechange,vulnerabilityandadaptationinNorthAfricawithfocusonMorocco.Agriculture,EcosystemsandEnvironment,156,12-26.SimonHA.1996b:TheSciencesoftheArtifi-cial.Cambridge,MA:MITPress.3rded.SimonHA.1999:Thepotlatchbetweenpoliticalscienceandeconomics.InCompetitionandCooperation:ConversationswithNobelistsaboutEconomicsandPoliticalScience,ed.JAlt,MLevi,EOstrom.Cambridge,UK:CambridgeUniv.Press.Smith,A.,QuanChu,H.,1994:AMulti-CriteriaApproachforAssessingStrategiesforAnticipatoryAdaptationtoClimateChange[draft].DecisionFocus,Inc,WashingtonDC.Smith,J.B.,1997:Settingprioritiesforadaptingtoclimatechange.GlobalEnviron.Change7,251–264.Smith,J.B.,Lenhart,S.S.,1996:Climatechangeadaptationpolicyoptions.Clim.Res.6,193–201.Spies,T.A.,T.W.Giesen,F.J.Swanson,J.F.Franklin,D.Lach,andK.N.Johnson,2010:ClimatechangeadaptationstrategiesforfederalforestsofthePacificNorthwest,USA:ecological,policy,andsocio-economicperspectives.LandscapeEcology,25(8),1185-1199.Stadelmann,M.,Michaelowa,A.,Butzengeiger-Geyer,S.,Köhler,M.,2011:Universalmetricstocomparetheeffectivenessofclimatechangeadaptationprojects.Paperpresentedatthe“ColoradoConferenceonEarthSystemGovernance:CrossingBoundariesandBuildingBridges“,17-20May2011,ColoradoStateUniversity,FortCollins.StaffordSmith,M.,L.Horrocks,A.Harvey,andC.Hamilton,2011:Rethinkingadaptationfora4°Cworld.PhilosophicalTransactionsoftheRoyalSocietyA,369,196-216.Stern,N.,2006:SternReview:EconomicsofClimateChange.CambridgeUniversityPress,Cambridge,UK,692pp.Stillwell,A.S.,M.E.Clayton,andM.E.Webber,2011:Technicalanalysisofariverbasin-basedmodelofadvancedpowerplantcoolingtechnologiesformitigatingwatermanagementchallenges.EnvironmentalResearchLetters,6,034015,doi:10.1088/1748-9326/6/3/034015.Stuart-Hill,S.andR.E.Schulze,2010:DoesSouthAfrica’swaterlawandpolicyallowforclimatechangeadaptation?ClimateandDevelopment,2(2),128-144.
97
SWD,2013:134final,CommissionStaffWorkingDocumentaccompanying,“CommunicationfromtheCommissiontotheEuropeanParliament,theCouncil,theEuropeanEconomicandSocialCommitteeandtheCommitteeoftheRegions,”anEUStrategyonadaptationtoclimatechange,EuropeanCommission(EC),Brussels,Belgium,54pp.Trope,Y.andN.Liberman,2003:Temporalconstrual.PsychologicalReview,110(3),403-421.Tversky,A.andE.Shafir,1992:Choiceunderconflict:thedynamicsofdeferreddecision.PsychologicalScience,3(6),358-361.UNDP,2005:AdaptationPolicyFrameworkforClimateChange:DevelopingStrategies,PoliciesandMeasures.Lim,B.,E.Spanger-Siegfried,I.Burton,E.MaloneandS.Huq(Eds).CambridgeUniversityPress,258p.UNEP,2014:TheAdaptationGapReport2014.UnitedNationsEnvironmentProgramme(UNEP),Nairobi.USCTI,2013:ClimateChangeAdaptationforCoralTriangleCommunities:GuideforVulnerabilityAssessmentandLocalEarlyActionPlanning(LEAPGuide).U.S.CoralTriangleInitiativeSupportProgram(USCTI),Bangkok,Thailand,144pp.WalkerW.etal,2013:AdaptorPerish:AReviewofPlanningApproachesforAdaptationunderDeepUncertainty,inSustainability2013,5,955-979.Walker,W.E.,Lempert,R.;Kwakkel,J.H.,2013:DeepUncertainty.InEncyclopediaofOper.Res.AndManagementScience,3rded.;Gass,S.,Fu,M.,Eds.;Springer:Berlin,Germany.Webb,R.andJ.Beh,2013:LeadingAdaptationPracticesandSupportStrategiesforAustralia:AnInternationalandAustralianReviewofProductsandTools.NationalClimateChangeAdaptationResearchFacility(NCCARF),GriffithUniversity,GoldCoastCampus,Southport,Australia,106pp.Wing,I.S.andK.Fisher-Vanden,2013:Confrontingthechallengeofintegratedassessmentofclimateadaptation:aconceptualframework.ClimaticChange,117(3),497-514.Young,O.2006:Verticalinterplayamongscaledependentresourceregimes.EcologyandSociety11(1):27.BehaviouraleconomicsBenartzi,S.,&Thaler,R.H.(1995).Myopiclossaversionandtheequitypremiumpuzzle.TheQuarterlyJournalofEconomics,110,73–92.doi:10.2307/2118511Besley,T.(2006).PrincipledAgents?ThePoliticalEconomyofGoodGovernment.Oxford:OxfordUniversityPress.Besley,T.,&Coate,S.(1997).Aneconomicmodelofrepresentativedemocracy.TheQuarterlyJournalofEconomics,112,85–114.doi:10.1162/003355397555136Buchanan,J.M.,&Tullock,G.(1962).TheCalculusofConsent:LogicalFoundationsofConstitutionalDemocracy.Foundations(p.388).doi:10.2307/1913055
98
Cardenas,J.C.,&Carpenter,J.(2008).Behaviouraldevelopmenteconomics:lessonsfromfieldlabsinthedevelopingworld.JournalofDevelopmentStudies.doi:10.1080/00220380701848327Gollier,C.(2002).Discountinganuncertainfuture.JournalofPublicEconomics,85,149–166.doi:10.1016/S0047-2727(01)00079-2Grossman,G.M.,&Helpman,E.(2001).SpecialInterestPolitics.Cambridge,Mass:MITPress.HMTreasury.(2003).TheGreenBook:AppraisalandEvaluationinCentralGovernment.HMSO.Kahneman,D.(2011).Thinking,FastandSlow.Macmillan.Kahneman,D.,Knetsch,J.,&Thaler,R.H.(1991).Anomalies—Theendowmenteffect,lossaversion,andstatus-quobias.JournalofEconomicPerspectives,5,193–206.Kahneman,D.,&Tversky,A.(1979).Prospecttheory:ananalysisofdecisionunderrisk.Econometrica,47,263–292.doi:10.1111/j.1536-7150.2011.00774.xKrueger,A.O.(1974).Thepoliticaleconomyoftherent-seekingsociety.TheAmericanEconomicReview,64,291–303.doi:10.2307/1808883Kydland,F.E.,&Prescott,E.C.(1977).Rulesratherthandiscretion:theinconsistencyofoptimalplans.JournalofPoliticalEconomy,85,473.doi:10.1086/260580Mullainathan,S.(2005).Developmenteconomicsthroughthelensofpsychology.InAnnualWorldBankConferenceinDevelopmentEconomics2005:LessonsofExperience.Washington,DC.Niskanen,W.A.(1971).Bureaucracyandrepresentativegovernment.Aldine-Atherton.Olson,M.(1965).TheLogicofCollectiveAction.Cambridge,MA:HarvardUniv.Press.Persson,T.,&Tabellini,G.(2000).PoliticalEconomics:ExplainingEconomicPolicy.Cambridge,Mass:MITpress.Prelec,D.,&Loewenstein,G.(1991).DecisionMakingOverTimeandUnderUncertainty:ACommonApproach.ManagementScience.doi:10.1287/mnsc.37.7.770Samuelson,W.,&Zeckhauser,R.(1988).Statusquobiasindecisionmaking.JournalofRiskandUncertainty,1,7–59.doi:10.1007/BF00055564Thaler,R.H.,&Sunstein,C.R.(2008).Nudge:ImprovingDecisionsAboutHealth,WealthandHappiness.YaleUniversityPress.Tullock,G.(1967).Thewelfarecostsoftariffs,monopolies,andtheft.EconomicInquiry,5(3),224–232.Tullock,G.(1980).Efficientrent-seeking.InI.Buchanan,R.Tollison,&G.Tullock(Eds.),TowardsaTheoryoftheRent-SeekingSociety.TexasA&MUniversityPress.Weitzman,M.L.(2001).Gammadiscounting.TheAmericanEconomicReview,91,260–271.doi:10.1126/science.151.3712.867-a
99
FrameworksDFID(2014),EarlyValue-for-MoneyAdaptation:DeliveringVfMAdaptationusingIterativeFrameworksandLow-RegretOptions,DFID,London.SamFankhauser,NicolaRanger,JonathanColmer,SusannahFisher,SwenjaSurminski,DavidStainforthandAndrewWilliamson(2013).AnIndependentNationalAdaptationProgrammeforEngland.PolicyBrief.PublishedbyCentreforClimateChangeEconomicsandPolicyandGranthamResearchInstituteonClimateChangeandtheEnvironment,March2013.FrontierEconomics(20130).TheEconomicsofClimateResilienceCA0401.March2013.NicolaRanger,N.,Millner,A.,Dietz,S.,Fankhauser,S.,Lopez,A.andG.Ruta(2010).AdaptationintheUK:adecision-makingprocess.PolicyBriefingNotefortheCommitteeonClimateChangeAdaptationSub-Committee.Ranger,N.(2013)TopicGuide.Adaptation:DecisionMakingUnderUncertainty.NicolaRangerandSu-LinGarbett-Shiels(2011).Howcandecision-makersindevelopingcountriesincorporateuncertaintyaboutfutureclimaterisksintoexistingplanningandpolicy-makingprocesses?CentreforClimateChangeEconomicsandPolicyGranthamResearchInstituteonClimateChangeandtheEnvironmentincollaborationwiththeWorldResourcesReport.