the effects of electric utility decoupling on energy efficiency
Post on 02-Jan-2017
214 Views
Preview:
TRANSCRIPT
TheEffectsofElectricUtilityDecouplingonEnergyEfficiency
JenyaKahnLang1
InpartialfulfillmentofaBachelorofArtsDegreeinEconomicsand
EnvironmentalAnalysis,
201112academicyear,PomonaCollege,Claremont,California
1IwouldliketothankProfessorBowmanCutterforhisencouragementandfeedbackthroughoutthecourseofthisproject.Hisconstantsupportanddirectionmadethisprojectapossibility.IamextremelyappreciativetoprofessorsJohnJurewitzandPierangeloDePaceforsharingtheirexpertiseintheirrespectivefieldswithme.IwouldalsoliketothankProfessorsGarySmith,EleanorBrown,andCharMillerfortheirindispensibleassistanceandenthusiasm.Finally,Icouldnotpossiblythankmyparentsenoughforalloftheirhelpovertheyearsandwiththisproject.
2
AbstractTraditionalutilityregulationexacerbatesenergyinefficiencybycreatinganincentivetoencourageoverconsumptionofenergy.Revenuedecouplingmechanismseliminatethisthroughputincentive,butcriticsarguethatdecoupledutilitieswillstillnotactivelypromoteenergyefficiency.ThispapermodelstheinterplaybetweenutilityDSMinvestmentandregulatorincentivesandstandards.Itexploresthehypothesisthatdecouplingmechanismsdecreaseresidentialelectricityconsumption,butonlythroughtheireffectonthelevel,directdemand‐reducingeffects,andindirectdemand‐reducingeffectsthroughpriceofDSMinvestment.Itthenempiricallyanalyzestheeffectsofdecouplingmechanismsonresidentialper‐customerelectricityuse.Thefindingssuggestthatdecouplingmechanismsdosignificantlydecreaseresidentialelectricityconsumptionoverall,butthatthissignificancedisappearswhentheeffectsofdecouplingmechanismsonretailelectricitypriceandDSMinvestmentareproperlyaccountedfor.Resultsindicatethatdecouplingmechanismsincreasethedirectandindirectdemand‐reducingeffectsofDSMinvestment.FindingsconcerningtherelationbetweendecouplingmechanismsandlevelofDSMspendingsuggestapositivecorrelation,buttheyareinconclusiveduetolimitedsamplesize.
3
TableofContents• Introduction_______________________________________________________________________4• LiteratureReview_________________________________________________________________7
o EnergyInefficiency________________________________________________________7o TraditionalRegulation____________________________________________________8o SuggestedSolutionsConcerningtheThroughputIncentive
andEnergyEfficiency____________________________________________________10o DecouplingMechanisms–Overview____________________________________12o ArgumentsfortheImplementationofDecouplingMechanisms_____14o ArgumentsAgainsttheImplementationofDecoupling
Mechanisms_______________________________________________________________16o BriefHistoryofDecouplingAdoptionintheU.S.______________________20o MeasuringtheEffectsofDSMandDecouplingonEnergyEfficiency_21
• ModelingDSMInvestmentIncentives__________________________________________23o Introduction______________________________________________________________23o PartA–TraditionalRegulation_________________________________________26o PartB–Decoupling______________________________________________________28o Conclusions_______________________________________________________________29
• TheoryandMethod_______________________________________________________________31o HypothesestobeTested_________________________________________________31o DataandMethods________________________________________________________33
• Results_____________________________________________________________________________38o OverallEffectsofDecouplingonConsumptionandPrice_____________38o EffectofDecouplingMechanismsonLevelofDSMSpending________40o EffectofDecouplingMechanismsontheDirectDemand‐Reducing
EffectsofDSMSpending_________________________________________________41o EffectofDecouplingMechanismsontheEfficacyofDSMInvestment
duetoitsIndirectEffectonConsumptionThroughPrice_____________42• RobustnessTests_________________________________________________________________43
o UseofanAnnualInstrumentalVariable________________________________43o Pre‐ExistingTrends______________________________________________________44o PotentialEndogeneityoftheDecouplingVariable____________________45
• Conclusions_______________________________________________________________________46• References________________________________________________________________________50• AppendixA________________________________________________________________________57• AppendixB________________________________________________________________________61
4
Introduction
Overconsumptionofenergyisthesourceoftwoofthelargestissuesfacing
today’sworld:globalclimatechange(Stern2008)andenergysecurity(Brookings
2011).Energydemandisincreasingworldwideandisprojectedtocontinue
increasing,atannualaverageratesofabout3.2%and1.1%foremergingand
matureeconomiesrespectively(AsifandMuneer2005).Asaresult,scientists
projectacontinuationofthetrendsofincreasingairpollution,especiallycarbon
dioxide(CO2)andotherGreenhouseGas(GHG)pollutionrelatedtoclimatechange,
andadecreasingstockofnon‐renewableenergysources(Smil2010).
Inefficientenergyuseisexacerbatingglobalclimatechange.Fossilfuel
combustionistheprimarycauseofthe80%increaseinCO2emissionsbetween
1970and2004(IPCC2007).Coal‐firedpowerplantsemitabout1tonofCO2for
everyMegawattofelectricityprovidedtocustomers(Hurleyetal.2008).Whilethe
exactcostsofglobalclimatechangearecurrentlyindebate,withnumerous
estimatesaround3‐5%ofgrossdomesticproduct(GDP)peryear,climatechangeis
arguablythelargestmarketfailurepresentintoday’sworld.Duetoenvironmental
andhealthexternalitiesassociatedwithGHGemissions,thecostsassociatedwith
failingtoadequatelymitigateclimatechangeconsiderablyexceedthemitigation
costs(Stern2006,AckermanandStanton2008).
Sincethemajorityoftheworld’senergycomesfromfinite,rapidlydepleting
sources(Smil2010),whicharelocatedinonlyafewspecificcountries,manypeople
worryaboutthesustainedattainabilityofenergy.TheUS,likemanyothercountries
includingChina,India,andUK,reliesheavilyonenergyimportationtofulfillits
growingdemand.USoilreservescouldsustainthecountry’sdemandforlessthan4
years(AsifandMuneer2005).Worldwide,fossilfuelsaregettingincreasingly
difficultandlesscost‐effectivetoobtainandconvertintousefulformsofenergy.
Inevitably,societywillneedtotransitiontoapost‐fossilfuelworld,butthereisalot
ofuncertaintyregardingthetiminganddetailsofthisprocess(Smil2010).
Whileproduction‐basedtechnologicaladvanceswillprobablybepartofthe
solution,increasedenergyefficiencyanddecreasedenergyconsumptionisessential
5
foreffectiveclimatechangemitigationandforimprovementstoenergysecurity.
Duetothescaleofnecessarycarbonstorage,itisunlikelythatpeoplecouldcapture
andstoreanadequatefractionofourcurrentcarbonemissionsthroughcarbon
sequestrationmethods(Bryce2010).Duringthecontinuedperiodofheavyreliance
onfossilfuels,therefore,asubstantialreductioninemissionsmustbearesultof
lowerdemandforenergyproduction.Furthermore,whiletherearemanypotential
sourcesofenergyinaninevitablepost‐fossilfuelenergyregime,theyarealllimited
inthepotentialusefulenergytheycouldprovidesociety.Expertsagreethatthe
futureenergyregimewillmostlikelyneedtocopewithlowerenergyandpower
densitiesbydecreasingenergyconsumption(Smil2010).Accordingtothe
EnvironmentalProtectionAgency(EPA)(2007),increasingenergyefficiencyin
residential,business,andindustrialsectorsisoneofthemostcost‐effectivewaysto
addresstheissuesofenergysecurity,airpollution,andclimatechange.
Therecurrentlyexistmanycost‐effectiveandnegativecostopportunitiesin
energyefficiency,but,forthemostpart,peopledonotseemtobecapitalizingon
theseopportunities(Gillingham,Newell,andPalmer2009).Forexample,many
consumershaveyettoreplacetheirinefficientincandescentlightbulbswith
efficientcompact‐fluorescentlightbulbs(CFL’s)orlight‐emittingdiode(LED)
fixtures,eventhoughdoingsowouldsavetheconsumermoneyanddecrease
energyuse(McKinsey2007;EnergyStar2012).Economistshavesuggesteda
multitudeofreasonsforthisabundanceofseeminglyirrationaldecision‐making.
Themainimplicationofthesestudiesisthatconsumersneedexternalassistancein
makingefficientenergydecisions.
Utilitypromotionofenergyefficiencyisvaluable.Utilitiespromoteenergy
efficiencythroughvariousdemand‐side‐management(DSM)programsthataimto
alterthelevelandtimingofconsumerenergyconsumption.Theseprogramsinclude
assistingconsumerspracticallyandfinanciallyininstallingenergyefficient
technologies,educatingconsumersaboutenergyconsumptionmanagement,and
institutingpricingschemesintendedtotransformconsumerincentives.DSM
programsexistforindustrial,commercial,andresidentialcustomers(Loughranand
6
Kulick2004).Gillingham,NewellandPalmer(2006)foundthatutility‐based
demand‐side‐management(DSM)programsproducedgreaterenergyreductions
thangovernmentorthird‐partyDSMefforts.TrainandStebel(1987)foundthat
peopleareskepticalthatspecificsupposedlyenergy‐efficientdeviceswillbecost‐
effectiveandthatthisskepticismisreducedwhenutilitiesofferrebates.
Undertraditionalenergyutilityregulation,however,utilitiesareincentivized
toencourageinefficientenergyuse.Thisphenomenonisknownasthethroughput
incentiveofelectricandnaturalgasutilities.Asitisasubstantialbarriertoutility
promotionofenergyefficiency,itisimportanttoaddressthisincentivestructure.
Onemechanismthatcanbeimplementedtoaddressthethroughput
incentiveissueandtherebyencourageenergyefficiencyisdecoupling,inwhich
revenuesarepartiallyorfullydetachedfromandunaffectedbysalesquantities.
Whileadecouplingmechanismeliminatesautility’saversiontodemandside
management(DSM),thereissomedebateoverwhetherthesemechanisms
encourageutilitiestoactivelyinvestinDSMandtopromoteenergyefficiency
(NARUC2007).
Thispaperaimstoaddressthequestionofwhetherdecouplingmechanisms
promoteenergy‐efficientpracticesandcost‐effectivechangesinenergy
consumptioninpracticethroughanalysisofhistoricaltrendsinenergy
consumption.Itbeginsbyreviewingtheexistingliteratureonthesubjectand
performingeconomicmodelingtoexploretheinterplaybetweenutilityDSM
investmentandregulatorincentivesandstandards.Econometrictechniquesare
thenutilizedtoanalyzetheempiricalrelationbetweendecouplingmechanismsand
residentialelectricityconsumption.Finally,thispaperaddressessomepotential
concernswiththeunderlyingassumptionsmadeinthisanalysisandpresentssome
robustnesstestsontheresults.
7
LiteratureReview
EnergyInefficiency
HeightenedawarenessabouttheharmfuleffectsofGHGemissionsand
widespreadconcernsaboutenergysecurityhavesparkedincreasedresearchon
energyefficiencyoverthepastfewdecades.Numerousacademicshaveattempted
touncoverthestructuralandbehavioralfactorsthataffectenergyconsumptionand
energyefficiencyinvestment(GlaeserandKahn2008,Baumann2008).Othershave
focusedonunderstandingthereasonsthatsomepeoplesupportenergyefficiency
measuresandchoosetoparticipateinenergyefficiencyprogramswhileothersdo
not(Musti,Kortum,andKockelman2011,KotchenandMoore2007,CostaandKahn
2010).
Despiteincreasedawarenessabouttheneedforenergyefficiencyand
improvedunderstandingofenergyefficientpractices,homeownersarenot
investinginenergyefficiencyasmuchastheyshould(Brennan2009b).Historically,
consumershaveactedasiftheyhadabout25%discountrateintheirchoicesof
investinginconservation,whichissubstantiallyhigherthanmostestimatesofthe
prevailingsocialdiscountrate(Hausman1979).Galluppollsthroughoutthepast
decadeshowthatAmericansbelievethatconservation,asopposedtoincreased
fossilfuelproduction,isthekeytoaddressingthenation’senergyproblems(Saad
2011).Brennan(2009b)attributesthisdiscrepancybetweenbeliefsandactionsto
consumerchoicefailure.Gillingham,Newell,andPalmer(2009)identifyheuristic
decision‐makingandboundedrationalityaspotentialcausesofconsumerchoice
failureregardingenergyefficiency.Inotherwords,decisionsconsumersmakeabout
energyefficiencyareoftenirrationalduetolackofavailableinformation,human
cognitivelimitations,thecognitiveburdenofdecision‐makingandthetimeittakes
tomakedecisions.Gillingham,Newell,andPalmer(2009)alsorecognizeprospect
theoryasapotentialbehavioralfailure.Prospecttheorystatesthatpeopleare
hesitanttochangetheirbehavior,suchasinvestinginenergyefficiencyiftheyare
unsureofthepotentialcostsandbenefitsbecausetheyaredisproportionately
aversetopotentiallossesrelativetopotentialgains.Gillingham,Newell,andPalmer
8
(2009)foundthatconsumersoftenignoreenergyefficiencyinpurchasingdecisions
becausetheycannotdistinguishbetweenproductsthataremoreenergyefficient
andproductsthatarelessenergyefficientsinceallproductsarebeingadvertisedas
beingenergyefficient.
Anothersourceofinefficienciesinenergyusestemsfromaconceptknownas
theprincipal‐agentproblem.Peoplewhouseenergyinabuildingyetdonotpay
utilitybills,suchasmanyrenters,havenoincentivetominimizetheirenergyuseor
toinvestinenergyefficiency.Theresidentsmakethedecisionabouthowmuch
energytoconsumeandhowmuchmoneytoinvestinfutureenergysavings,but
theydonotexperienceanyoftheprivatecostsoftheirchosenactions.Asaresult,
theytendtoover‐consumeandunder‐investcomparedtotheefficientsetofactions
(Gillingham,Newell,&Palmer2009).IncreasedutilityDSMprogramsmay
somewhatincreasetheenergyefficiencyofsuchresidentsduetoenvironmental
consciousness,butneitherDSMprogramsnorutilitypricestructurestacklethecore
inefficiencyoftheprincipal‐agentissue.
TraditionalRegulation
Undertraditionalregulation,theratesofanelectricutilityareestablishedby
anexternalpartyduringageneralratecase,whichusuallyoccurevery3‐6years,or,
insomestatesonlyattherequestoftheutility(OhioPUCO2011,WisconsinPSC
2001).
Inaratecase,thethirdpartyexaminesalloftheutility’sexpensesduringa
pastorfuturetestyear,hearstestimoniesfromallinterestedparties,and
determinesarevenuerequirement,ortherevenuenecessarytocovertheutility’s
expensesandtaxesandtogiveafairrateofreturnoninvestment(Lazer,Weston,
andShirley2011,OhioPUCO2011,WisconsinPSC2001).Fixedcostsandcosts
associatedwithdepreciationareincludedinthedeterminationofutilityexpenses
(EPA2007).Thethirdpartyregulatoroftenholdsformalhearingtohear
testimoniesofallinterestedparties,includingutilityrepresentatives,customers,
andinvestors.Inmanystates,theutilitiescanapplyforarehearingiftheyare
9
dissatisfiedwiththeregulator’sdecision.Insomeextremecases,utilitiescaneven
bringratecasestothestatesupremecourt(OhioPUCO2011).
Oncearevenuerequirementisfinalized,theallowedrevenueisthendivided
bythenumberofunitsofelectricitysold(orexpectedtobesold)duringthetest
periodinordertodeterminetheutility’saverageelectricityrateforthenextperiod.
Theaverageratesareoftencomputedseparatelyforeachcustomerclass2.These
averageratesareessentiallyconstantuntiltheutilitynextundergoesaratecase.
(Lazer,Weston,andShirley2011)
Onenotableaspectofanelectricutility’scoststructureisthattheutility
incursvirtuallynonetmarginalcostsperunitofelectricityproduced.Thepotential
marginalcostsofautilitywouldbelabor,distribution,andfuelcosts.However,
laboranddistributioncostsvarywithnumberandlocationofcustomersandare
essentiallynotaffectedbyper‐customerenergyuse.Theonlycostsrelatedto
energyusearefuelcosts,butthesearepassthroughs,orcoststhataredirectly
transferredtocustomers.Variationinfuelcostsusuallyappearsasamonthlytariff
orcreditoncustomerbills,oftenreferredtoasfueladjustmentclausesorpowercost
adjustments(EnerStar2012).Eachmonth,theutilityrecalculatesthefuelcost
associatedwitheachcustomerbasedonthemonth’sfuelpricesandthecustomer’s
electricityconsumptionandchargesthecustomerexactlythatamount.
Anothernotableaspectofatraditionallyregulatedutility’sratestructureis
thatifactualrevenueduringthetimeperiodbetweenratecasesdiffersfrom
expectedrevenueforanyreasonnotcoveredbyadjustmentclauses,theutilitygains
aprofitorsuffersaloss.Utilitieshavesubstantialfixedcoststhatrequireadequate
revenuetofinance.Theseincludesunkcapitalcostsassociatedwithincreasing
generationcapacity,buildingtransmissionlines,andDSMinvestments.Ifrevenue
doesnotreachthethresholdvalueofcoveringfixedcosts,theutilitysuffersaloss.
(CSI2008)
2Manyutilitiesvaryrateschedulesbycustomerclass.Customerclassesgroupcustomerswithsimilardemandcharacteristicstogether(ex‐small,residentialcustomers).
10
Underthetraditionalstructureofregulation,utilitiesaredeterredfrom
investinginenergyefficiencyandevenhaveincentivestoactivelylobbyagainst
energyefficiencyinfavorofdecreasingefficiency.Brennan(2008)arguesthat
utilitiesonlyhaveincentivestopromoteenergyefficiencyandotherdemand‐
reductionsifpricecapscausepricestofallbelowmarginalcostsbutthatwhen
pricesaregreaterthanmarginalcosts,utilitieshaveincentivestoincrease
throughputi.e.electricityusage.Inalmostallinstances,regulatedretailpricesdo
surmountmarginalcosts(EIA1997).Thus,intheperiodsbetweenratecases,the
utilityhasanincentivetoincreaserevenuesabovewhathadbeenexpectedbythe
ratessetbyincreasingelectricitysold.Thisisknownasathroughputincentiveand
isamajorbarriertotheutilitypromotionofenergyefficiency(EPA2007).
Increasedenergyefficiencydecreasesthroughput,sotheutilitieshaveanincentive
toactivelyopposeenergyefficiencyprograms.Ifutilitiesneverthelessdocreate
programstopromoteenergyefficiency,notonlydotheyloserevenuesfrom
electricitysales,buttheyalsohavetocoverspendingonprogramimplementation.
Thiscanleadtolosses(knownaslostmarginrecovery).AninvestigationbyIdaho
PowerCompanyfoundthat,inpractice,revenuelossfromenergyefficiency
programsdoesindeeddecreaseautility’srecoveryoffixedcosts,whichproduces
barrierstoutilityinvestmentindemand‐reducingenergyefficiencyprograms(EPA
2007).
SuggestedSolutionsConcerningtheThroughputIncentiveandEnergyEfficiency
Thissectionbrieflydiscussesthemeritsanddrawbacksoffourprominent
proposalsforaddressingthethroughputincentiveproblem:governmentmonetary
incentives,othertypesofthirdpartypromotionmechanisms,straightfixed‐variable
ratedesigns,andreal‐timepricing.
Oneproposalisthatthegovernmentshouldprovidemonetaryincentivesto
utilitiesforinvestinginenergyefficiency.Whilethiswouldassistincoveringthe
costsofutility‐sponsoredDSMprograms,monetaryincentivesalonewould
probablynotbeeffective,astheincentivemustbesufficienttocoverthecostsof
11
programimplementationandcompensateforlostmargins.Suchincentives,ifnot
designedwithadequatecare,mayalsocauseutilitiestoinvestalotofmoneyin
energyefficiencyprogramsthatarenotparticularlycost‐effective(Lazer,Weston,
andShirley2011).
Moregenerally,manypromotersofenergyefficiencyarguethatathirdparty,
andnotutilities,shouldberesponsibleforencouragingenergyefficiency.They
contendthatutilitiesareinnatelynotinthebestpositiontopromoteenergy
efficiency.Utilitieshaveanadvantageoverthird‐partyenergy‐efficiencyproviders,
however,astheyhavemorecompleteinformationandrecordsaboutenergyuse.
Moreimportantly,athird‐partyenergy‐efficiencyproviderwouldbemosteffective
iftheutility’sthroughputincentivecouldbeeliminated(bydecoupling,for
instance),asthiswoulderadicatelobbyingagainstthethirdpartyandwould
increasethelikelihoodofrelevantinformationdisclosure.InVermontandOregon,
third‐partyenergy‐efficiencyprovidersfounddecouplingtobeahelpfuladditionto
theirownencouragementofenergyefficiency(Lazer,Weston,andShirley2011).
Anotherproposalisimplementationofastraightfixed‐variable(SFV)rate
design(Lesh2009).UnderSFV,thereisalargemandatory,non‐volume‐based
chargeforallcustomersthatcoversallormostoftheutility’sfixedcosts,rendering
variablecostsclosertothetruemarginalcostofproducingelectricity.This
decreasesandcaneveneliminatethethroughputincentive.However,SFVrate
designssimultaneouslydiscourageenergyefficiencybydecreasingtheincentivefor
consumerstoreducetheirenergyusethroughlowerusage(marginal)costs.In
addition,SFVisregressive(EPA2007).Sincelow‐incomehouseholdstendto
consumelessenergy,alargerfixedchargewilldisproportionatelyburdenlow‐
incomehouseholds.Boonin(2009)promotesaSFVdesigncombinedwitha
Revenue‐NeutralEnergyEfficiencyFeebate(REEF),whichtheoreticallycounteracts
theregressivenatureoftheSFVdesignandreestablishescustomerincentivesto
decreaseenergyuse.Unfortunately,itmaybedifficultandadministrativelycostlyto
constructafeebatesystemthataccuratelydeterminesindividualenergyefficiency
andappropriatelycounteractstheregressivenatureofSFV.
12
Realtimepricing(RTP)ofelectricityhasbeensuggestedasamethodof
increasingenergyefficiency,limitingmarketpowerofutilities,andreducing
electricitydemandvariance(HollandandMansur2008).WithRTP,utilitiesset
pricesasafunctionofactualdemandatthegiventime.Accordingtoeconomic
theory,thiscausesadisincentivetouseelectricityduringhoursofpeakdemand,
which,duetovariabilityinefficiencyofgenerationequipment,shouldhavea
disproportionatepositiveeffectontheenvironment(HollandandMansur2008).In
contrast,Ito(2010)foundthatactualhousehold‐electricity‐usedatasuggeststhat
consumersrespondtoaveragepricesinsteadofmarginalprices,whichlowers
projectedestimatesofdecreasesinpeakdemandduetoRTP.
DecouplingMechanismsOverview
Decouplingmechanismsaddressthethroughputincentivebyfullyor
partiallydetachingutilityrevenuesfromsales.Underadecouplingmechanism,the
allowedrevenuesaresetduringageneralratecase,andratesareadjustedduring
regular,periodictrueupsthatkeeplongrunrevenueequaltoallowedrevenueby
changingprices.Iftheutilitymakeslessrevenuethanexpectedinagivenperiod,
thenratesareincreasedorasurchargeisaddedinthefollowingperiod.Conversely,
ifthereisasurplusinrevenue,themoneyisrefundedtothecustomersintheform
oflowerrates,lumpsumtariffs,orotherreconciliationmechanisms(EPA2007).
Notethatnoreassessmentsofcostsorallowedrevenueareperformedduringtrue‐
ups(Lazer,Weston,andShirley2011).
Thereareavarietyofdecouplingmechanisms.Onedifferencebetweenthem
istheeffectofincreasingtheutility’scustomerbase.Understraightrevenue
decoupling,anincreaseincustomersdoesnotchangeautility’sallowedrevenues
and,asaresult,tendstohurtratherthanhelptheutility.Revenuepercustomer
(RPC)decoupling,however,fixesallowedrevenuepercustomer.Thusallowed
revenueduringanygiventimeperiodisdeterminedbythefollowingformula:
AllowedRevenue=(AllowedRevenuesperCustomer)*(#ofCustomers)
13
RPCdecouplingcoulddiscourageutilitiesfromincreasingtheircustomerbaseif
newcustomerswerehigherenergyusers.SomeRPCdecouplingmechanisms
addressthisissuebyincludingdifferentallowedRPC’sfornewandexisting
customers.(Lazer,Weston,andShirley2011)
Decouplingmechanismsalsodifferwithregardtothefrequencyoftrue‐ups.
Utilitieswithaccrualdecouplingmechanismsonlyundergoannualtrue‐ups,while
thosewithcurrentdecouplingexperiencetrue‐upseverybillingperiod.True‐upsfor
otherdecoupledutilitiesmayoccuronaquarter‐orsemi‐annualbasis(Lazer,
Weston,andShirley2011).
Anotherwaydecouplingschemesdifferisbythereasonsallowedfor
revenueadjustmentsduringtrue‐ups.Afullydecoupledutilityadjustsforany
deviationofactualrevenuesfromallowedrevenues,regardlessofthecauseofthese
deviations.Autilitywithpartialdecouplingadjustsforacertain,fixedpercentageof
thedepartureofactualrevenuefromallowedrevenuesduringtrue‐ups.Partial
decouplingmechanismsalsodonotdiscriminatebasedoncauseofrevenue
deviations.Partialdecouplingreducesthethroughputincentivewithoutcompletely
eliminatingit.Duringatrue‐upforautilitywithlimiteddecoupling,disparities
betweenactualrevenuesandallowedrevenuesmayormaynotleadtoadjustments
dependingonthecauseofthedisparities.Onecommonexampleoflimited
decouplingisutilitiesthathaveonlylostmarginmechanisms,whereadjustmentsfor
revenuedecreasesareonlymadeifthedecreasescanbeexplicitlyidentifiedasthe
resultofDSMprograms.Ifexecutedcorrectly,limiteddecouplingeliminatesthe
throughputdisincentiveassociatedwithenergyefficiencyprogramswithout
eliminatingutilityresponsibilitytoprovidecoverageandassumeriskduetoother
causes,suchaseconomicfluctuations.Thelargestdrawbackoflimiteddecouplingis
itsrelativelyhighadministrativeandmonitoringcostscomparedtootherformsof
decoupling(Lazer,Weston,andShirley2011).
Otherdecouplingmechanismsincludeattritionadjustments,inflationminus
productivityadjustments,andKfactoradjustments.Attritionadjustmentsare
14
essentiallyannualabbreviatedratecaseswhenallowedrevenuesarereassessed
andalteredslightlyinresponsetoknownandmeasurablechangesinautility’s
costs.Thismechanismdecreasestheneedforfrequentfullratecasesifautility
doesnotundergoalargestructuralchange.Inflationminusproductivityadjustments
alterallowedrevenuesinresponsetoshiftsininflationorproductivity.This
mechanism,alongwithregulartrue‐ups,alsodecreasestheneedforfrequentfull
ratecases.Anothermechanismtochangeallowedrevenuesbetweenratecasesis
knownasKfactoradjustment.AKfactoradjustmentisapredetermined,usually
annual,rateincreaseordecreasebetweenratecases.Forexample,autilitymight
receivea1%annualincreaseinallowedrevenuesbetweenratecases.TheKfactor
itselfcanbedesignedtochangeovertimeifgrowthisnotpredictedtobelinear,or
canbeappliedtoallowedrevenuespercustomerinsteadoftotalallowedrevenues.
Althoughallthreeofthesemechanismsaimtoreducetheneedforfrequentrate
cases,occasionalratecasesarestillnecessarywithallthreeofthesedecoupling
mechanisms.
ArgumentsfortheImplementationofDecouplingMechanisms
Decouplingmechanismsareattractiveforseveralreasons.Theyare
beneficialtotheenvironment(GraniereandCooley1994)andaremorepolitically
feasiblethanmanymechanismstopromoteenergyefficiency.Theyencourage
energyefficiencybyeliminatingapoliticalbarriertoenergyefficiencypromotion,
removinganeconomicbarriertoutilityenergyefficiencyinvestment,andpartially
shiftingtheresponsibilityofmakingenergyefficiencydecisionsfromconsumersto
suppliers.Decouplingmechanismsarepoliticallyfeasible,astheyinvolverelatively
lowadministrativecostsandarestructuredinawaythatfostersutilitysupport.
Fromanenergy‐efficiencystandpoint,thedecoupling‐causedeliminationor
reductionintheutilitythroughputincentiveisessentialforutilityorthird‐party
promotionenergyefficiency.Forone,theremovalofathroughputdisincentive
decreasesoreliminatesutilities’politicaloppositiontopublicenergyefficiency
programsandgovernmentmeasures(Brennan2009a).Moreover,thedecoupling
15
incentivestructurealsorendersutilitiesmorewillingtotakeactionsthemselves
thatencourageenergyefficiency.Forinstance,underdecouplingmechanisms,
utilitiesaremorewillingtoinstituteratedesignsthatencourageenergyefficiency
(Lazer,Weston,andShirley2011).
Brennan(2008,2009a)arguesthatdecouplingisfundamentallyabout
transferringresponsibilityforenergyefficiencydecisionsfromconsumersto
suppliers.Asdiscussedabove,manyconsumersdonothavethetoolstomake
rationaldecisionsregardingenergyefficiency,bututilityandgovernmentDSM
programscanreducesomeofthecognitivebarriersbyusingconsumerfinancial
incentivestopromotemoreefficientlevelsofenergyconsumptionandbysupplying
informationaboutspecificenergyefficiencymeasuresandtheircalculatedeffects.
Fullandpartialdecouplingmechanismstendtobepoliticallyfeasible,
partiallybecausetheyrequirerelativelylowadministrativecost.Unlikesome
alternativeenergy‐efficiencypromotionmethods,decouplingmechanismsdonot
requireregulatorstoevaluatetheefficacyofenergyefficiencyprograms.
Furthermore,decouplingmechanismsreducetheneedforfrequentratecasesand
avoidtheassociatedcosts(EPA2007).Theonlypubliccostofadecoupling
mechanismisthetimeittakesstateemployeestolearnaboutthenewsystemand
establishproperregulations(CSI2008).
Anotherreasonforthepoliticalfeasibilityofdecouplingmechanismsistheir
tendencytoattainutilitysupport.Utilitiestendtosupportdecouplingbecauseit
stabilizestheirrevenuesandthusreducestheirrisksassociatedwithrevenue
volatility.Thisdecreasestheircostsofcapital,bothintermsofinterestratesand
equityreturnsrequired(Lazer,Weston,andShirley2011).Inaddition,utilities
oftenpreferdecouplingtotraditionalregulationbecausetheybelievethatthe
traditionalratecasesdonottakeallreal‐worldfactorsintoaccountintheir
predictionsandcalculationsofraterequirements,leadingtoearningsthatarelower
thanauthorizedearningsafewyearsaftertheratecase(Costello2011).
16
ArgumentsAgainsttheImplementationofDecouplingMechanisms
Opponentsofdecouplinghavevoicedseveralconcernsaboutdecoupling
mechanisms.Theyareskepticalabouttheefficacyofdecouplingmechanismsin
promotingenergyefficiency.Thissectiondiscussesthecurrentdebatessurrounding
thesepotentialdrawbacksofdecouplingmechanismsandincludespolicy
suggestionstomitigatethesedrawbacks,whenapplicable.
Onecategoryofcritiquesofdecouplingmechanismsisthattheyfailto
provideanincentiveforenergyefficiencyinvestment.Manyexpertsarguethat,
althoughdecouplingmechanismswilleliminatetheincentivetoactivelyincrease
energyconsumption,utilitieswillstillfailtopursueenergyefficiencybecause
supply‐sideinvestmentswillcontinuetobemoreattractivetothemthanDSM
investments(Kihm2009).Historically,utilitieshavegainedfromsupply‐side
investmentsbecausetraditionalratesettinghasdefactoallowedmorethana
normalrateofreturnontheseinvestments.IfinvestmentsinDSMdonotprovide
comparablereturns,forinstancebecausetheycausedecreasedfuturedemandfor
utilityservice,itwouldpresumablybemoredifficultforautilitytoattractfunding
forDSMinvestmentsthanforsupply‐sideinvestments(EPA2007).
Kihm(2009)arguesthatevenifDSMperformanceincentivesforutilities
werelargeenoughtoprovidecomparableratesofreturnforDSMandsupply‐side
investments,manyutilitieswouldcontinuetoprefersupply‐sideinvestments
becausetheyarelargerinscale.Utilitieshavehistoricallypreferredlargerscale
investmentstosmallerscaleinvestments,aconceptknownastheAverch‐Johnson
(A‐J)hypothesis.Thispreferenceoftenremainsevenwithchoicesinvolvingalarge‐
scaleinvestmentwithalowerrateofreturnthananalternativesmall‐scale
investmentsuchasDSMinvestments.Kihmarguesthatdecouplingonlyworksfor
utilitiesnotsubjecttotheA‐Jeffect,orutilitieswithallowedratesofreturncloseto
thecostofcapital,anditisunlikelythatmostutilitiesfallintothiscategory.Finally,
utilitymanagersandregulatorshavehistoricallybackedexpansionsinfuture
electricitygenerationcapacitybecausetheriskstotheutilityoffutureinadequate
electricitysuppliesarehigherthantheriskofhavingexcesscapacity.(Kihm2009)
17
Ontheotherhand,thereareseveralreasonsthatadecoupledutilitymay
preferDSMinvestmentstosupply‐sideinvestments,evenwithoutthepresenceof
performanceincentives.Fromacustomerservicestandpoint,DSMinvestments
improvethepublic’sviewoftheutility,enablemorepositiveutility‐customer
interactionthansupply‐sideinvestments,andgeneratelesspoliticaloppositionthan
supply‐sideinvestments.Supply‐sideinvestmentsusuallyinvolvebuilding
pollution‐emittingpowerplantsnearspecificcommunities,whomayresistthe
projectorrequestcompensationforitsundesirableeffects(Bloomquist1974).
Conversely,DSMinvestmentsdonotseverelyadverselyimpactaconcentrated
groupofpeople;theyusuallysubstantiallyhelpaconcentratednumberofpeople–
thecustomerswhochoosetoparticipateintheDSMprograms–ataminutecostto
many(ECW1997).Asaresult,DSMinvestmentswilloftengeneratelesspolitical
oppositionthansupply‐sideinvestments.Theutilitycanevencapitalizeonthis
distributionofcostsandbenefitsandimproveitspublicratingsbypublicizingthe
savingsofthecustomerswhobenefitthemost.
Moreover,withtheuncertaintyofthefutureenergyregime,DSM
investmentsmayactuallyattractinvestmentmorethansupply‐sideinvestments
duetotherelativeeffectsonriskandenergysecurity.Reducedenergyconsumption
anddecreaseddependenceonenergyfromout‐of‐stateoroverseasourcesrenders
autilitylesssusceptibletounexpectedfuturechanges.Theseincludeunanticipated
capitalcostincreases,increasesinenergyregulationstringency,transportationcost
increases,andpoliticallyoreconomically‐inducedfossilfuelsupplyshortages.
(Hurleyetal.2008,EPA2007)
Opponentsofdecouplingarealsoskepticalofitsefficacyinpromoting
energyefficiencybecauseitcreatesadisincentiveforconsumerenergyefficiency
investments.Theyarguethatdecouplingmechanismsdiscouragecustomersto
decreaseelectricityusebecausedoingsowillcauseafutureincreaseinelectricity
rates(GraniereandCooley1994).However,eachindividual’seffectonthepriceis
trivial.Thus,fortheindividual,decreasedconsumptionoutweighsanyeffectoftheir
ownbehavioronrates(NARUC2007).Themonetarybenefitsofreducing
18
consumptionareveryconcentrated,whilethecorrespondingcostsfromthe
associatedrateincreasearewidespread.Asaresult,eachcustomernotonlyhasan
incentivetoreduceconsumption,butalsohasanincentivetoreduceconsumption
evenmoresubstantiallythantheothercustomers(ECW1997).
Finally,decouplingmechanismshavelimitedefficacybecausetheyfailto
addresssomeimportantcausesofenergyinefficiency.Theprincipal‐agentproblem
stillexistsinthepresenceofdecouplingmechanismssinceconsumerswhodonot
payfortheirenergyusestilllackincentivestodecreasethisuseunderdecoupling
(Gillingham,Newell,andPalmer2009).Similarly,theadoptionofdecouplingdoes
notsolveconsumerchoicefailuresandmanyconsumerswhowouldbenefitfrom
energyefficiencychangeswillnotmakethosechanges,whetherornottheirutility
possessesadecouplingmechanism(Brennan2008).
Inaddition,opponentsofdecouplingworrythatthemechanismwillincrease
thevolatilityofelectricityratesandcausefrequent,significantrateincreases(Lesh
2009).GraniereandCooley(1994)didanumericalstudyonthisissueand
concludedthat,“ratepayersmighthavetodealwithsubstantialvolatility.”Onthe
otherhand,Eto,Stoft,andBelden(1994)foundthatERAM,California’decoupling
mechanism,reducedratevolatilityandhadanegligibleeffectonratelevels.
Similarly,Lesh(2009)foundthatdecouplingadjustmentstendtobeverysmall
relativetoresidentialretailrates,withnosignificantupwardordownwardtrendin
rates.Comparedtootheradjustmentfactorsonbills,suchasfuelandpurchased‐
poweradjustmentclauses,volume‐balancingdecouplingadjustmentstendtoalter
rateslessdrastically(Lazer,Weston,andShirley2011).
Moreover,evenifelectricityratesdoincrease,thereisabeneficialaspectto
thisinthatitadjustsforthenegativeexternalitiesontheenvironment.Michelfelder
(1993)foundthatelectricityratesareconsistentlybelowmarginalsocialcostsof
producingelectricity.Thus,increasingelectricitypricesactuallybringsthemcloser
tothelong‐runmarginalsocialcostofelectricityproduction,whichultimately
benefitsratepayers(GraniereandCooley1994).Furthermore,Bholeetal.(2011)
foundsignificantpositivecorrelationbetweenelectricitypricesandstateenergy
19
efficiencyexpenditures,especiallyaboveathresholdpricelevel.Heproposedthat
higherelectricitypricesincreasethecost‐effectivenessofDSMprograms.In
addition,Linn(2008)contendsthathigherenergypricesincreasetheprobability
thatplantsadoptnewenergyefficiencytechnologies,especiallyfornewplants,
althoughKahnandMansur(2011)suggestthatnewplantsinenergy‐intensive
industrieswouldfactorelectricitypricesintotheirlocationdecisionandspecifically
chooseageographicallocationwhereelectricitypriceswerelower.TheCenterfor
StateInnovation(2008)arguesthat,whiledecouplingmechanismsmayincrease
energycostsforsomecustomersintheshortrun,thediminishedneedfornew
powerplantsduetoreducedenergydemandwillultimatelylowerratestoall
customers.
Opponentsofdecouplingareparticularlyconcernedaboutdecoupling
mechanismsshiftingweatherandeconomicrisksfromutilitiestoconsumersinthe
formofratevolatility(Meneken2007).Theyarguethatutilitiesbearnoneofthe
costsassociatedwithextremeweatheroreconomicrecessionsunderdecoupling.
TheypointtoMaine’sbriefexperiencewithadecouplingmechanismasanexample.
ShortlyafterCentralMainePoweradoptedafulldecouplingmechanismin1991,
Mainefellintoarecession.Requiredrevenuesweretoohigh,astheyhadbeenset
basedonatrialperiodduringathrivingeconomy.Thus,pricesincreaseddrastically
asenergyconsumptionfell,andcustomersborethefullburdenoftherecession
whileCentralMainePoweremergedunscathed.Thedecouplingmechanismwas
ultimatelyterminatedduetoanimositytowardsthemechanismproducedbythis
incident.Manycustomersbelievedthetruepurposeofthemechanismwastoshift
riskfromutilitiestocustomers.(EPA2007)
AreportfromtheEPA(2007)conteststhatthisriskshiftisinherentto
decouplingandarguesthattheexistenceandmagnitudeofthisriskshiftvarieswith
thedecouplingdesign.Lazer,Weston,andShirley(2011)completelydismissthe
argumentthatdecouplingshiftsweatherriskstoconsumersunderfullandpartial
decouplingmechanismsandarguethatdecouplingdecreasestheriskforutilities
andconsumers.Ifanextremeweathereventcausespeopletoconsumemore
20
electricity,decouplingcausesratestodecrease,makingtheenergyconsumption
moreaffordableforconsumers.Lazer,Weston,andShirley(2011)doadmitthat
decouplingexacerbateseffectsofrecessions,buttheyarguethatgeneralratecases
dosoaswell.Theysuggestcombiningdecouplingwithacaponrateincreasesto
preventsituationsliketheonethatoccurredinMaine.
Someopponentsofdecouplingmayarguethatdecouplingisregressive.Low‐
incomecustomerstendtohavelesselectricityreductionpotentialthanhigher‐
incomeusers.Whiletheydonotreapmanyofthebenefitsofreducedelectricityuse
duetoenergyefficiencyprograms,theyarestillsubjecttothehigherratescaused
bytheoverallreduceddemand(Lesh2009).Toaddressthepotentialconcernof
increasedshortruncostsforlow‐incomecustomers,mostdecoupledutilitiesoffer
lowerratestolow‐incomecustomersanddofundingandsurchargingonacustomer
class,orrateschedule,basis(Lesh2009).
Otherconcernsregardingdecouplingincludethelackofincentiveforutilities
torestoreserviceafterastormandincreasedregulatorycostsduetofrequenttrue‐
ups.Thesearebothfoundedyetnotparticularlycompellingconcerns.Thefirstissue
caneasilybeaddressedthroughadditionalrequirementsorincentivesinthedesign
ofthedecouplingmechanism(Lazer,Weston,andShirley2011).Periodictrue‐ups
doproduceadministrativeandregulatorycosts,buttrue‐upsareless
administrativelycostlythanratecases.Theincreasedregulatorycostduetotrue‐
upsisoffsettosomedegreebyareductionintheneedforfrequentratecasesand
theirassociatedcosts(EPA2007).
BriefHistoryofDecouplingAdoptionintheU.S.
DecouplingmechanismshavebeenoperationalintheUnitedStatessince
1978,whenPacificGas&Electricdecouplednaturalgassales(AGA2007).Four
yearslater,PG&EalsoimplementedadecouplingmechanismknownastheElectric
RateAdjustmentMechanism(ERAM),forelectricitysales(McCarthy2009).Other
Californianutilitiesadoptedsimilarmechanismsshortlythereafter.Intheearly
1990’s,Maine,NewYork,andWashingtonalsoadopteddecouplingmechanisms,
21
althoughMainediscontinueditsmechanismafterabrieftrialperiod(Etoetal.1994,
EPA2007).BySeptember2007,atleastonenaturalgasorelectricutilityin16
stateshadimplementedadecouplingmechanism,anddecouplingmechanismswere
pendingin12morestates(EPA2007).AsofJune2011,utilitiesinabout28states
hadadoptedadecouplingmechanism,anddecouplingmechanismimplementation
decisionswerependingin12morestates(Lazer,Weston,andShirley2011,ACEEE
2011).
MeasuringtheEffectsofDSMandDecouplingonEnergyEfficiency
Thereexistsmuchdebateintheliteratureabouthowtomeasuretheefficacy
ofDSMprograms.Thetrueprogrameffectscannotbemeasuredbysolelyanalyzing
theobservedchangeinenergyconsumptionofcustomerswhoparticipateinthe
DSMprograms.Ononehand,JoskowandMarron(1992)arguethatsavingsofutility
DSMprogramstendtobeoverstatedduetooverlyoptimisticequipmentlifetimes
andtheexistenceoffreeriders,orprogramparticipantswhowouldhaveinvestedin
energyefficiencyevenwithoututilityinvolvement.Ontheotherhand,manyDSM
programanalystsworryabouttheopposite:understatingthebenefitsofDSM
programs.Programparticipantsmaydiscussenergyefficientbehaviorand
technologywithnon‐participants,whoconsequentlydecreasetheirenergyuse
withoutanyadditionaldirectutilityinvestment.Forexample,acustomermight
experiencehugereductionsinheatingandcoolingcostsafterusingautilityrebate
toaddatticinsulationinherhome,raveaboutthisexperiencetoafriendwhoisnot
eligiblefortherebate,andconvincethefriendtoinstallatticinsulationaswell.
Thesenon‐programparticipantsarecommonlyreferredtoasfreedrivers
(Gillinghametal.2009).Duemostlikelytomeasurementdifferences,Parformak
andLave(1996)foundthat99%ofutility‐reportedestimatesofsavingsfromDSM
arefairlyaccurateifonecontrolsforprice,weather,&economicactivity,while
LoughranandKulick(2004)foundthatutilityestimatesofelectricitysavingsdueto
DSMinvestmentaremuchlargerthanthetruesavings.Gowever,Auffhammeretal.
22
(2008)pointedoutflawsinLoughranandKulick’smethods.Thus,thereisno
consensusonthereliabilityofutilitysavingsestimatesfromDSM.
Thecurrentliteraturelacksexpostempiricalanalysisthatusesrecentdatato
measuretheeffectsofdecouplingmechanismsonenergydemand.Paststudieson
theimpactsofdecouplingmechanismsonenergydemandhavebeenalmost
exclusivelybasedonexanteeconomicmodeling.PaststudiesofDSMprograms,
however,haveincludedbothexanteeconomicmodelingandexpostempirical
studiesoftheimpactofDSMprogramsonenergyefficiency.Probablyduetothe
uncertaintiessurroundingmeasuringsavingsfromenergyefficiency,thereappears
tobeadiscrepancyindemandreductionestimatesbetweentheseexpostandex
antestudies.Forexample,studiesofthecost‐effectivenessofutilityDSMprograms
thatuseexpostempiricalanalysistendtofindprogramslesscost‐effectivethan
thosethatrelyprimarilyonexantemethods(Arimuraetal.2011).Intermsof
researchontheimpactofdecouplingmechanismsonenergyefficiency,thissuggests
thatresultsfromexantemodelsmaydiffersignificantlyfromthetrueeffects.Thus,
thereisaneedforexpostempiricalstudiesontheimpactofdecouplingmechanisms
onenergydemand.
Factorsthatarecommonlybelievedtoaffectresidentialelectricitydemand
includeDSMspendingincurrentandpreviousyears,economicactivitylevel,energy
prices,weatherconditions,andenvironmentalsensitivity,orthegenerallevelof
concernofcustomersabouttheenvironment(Delmasetal.2005,Arimuraetal.
2011).JaffeandStavins(1995)developedafunctionalformfortherelationbetween
DSMspendingandelectricitydemandthattakesintoaccountthenonlinearrelation.
Arimuraetal.(2009)pointedoutapossibleendogeneityissueinmodelsof
electricitydemandwithDSMspendingconsideredanexogenousvariable.They
wereconcernedthatlevelofDSMspendingmaybecorrelatedwithunexplained
fluctuationsindemand.TheyattemptedtouseTwo‐StageLeastSquares(2SLS)
estimationandinstrumentforDSMspending.However,theirresultsdonotsupport
thehypothesisthatDSMspendingisendogenous(Arimuraetal.2011).
23
Arimuraetal.(2011)conductedafairlythoroughanalysisonthecost‐
effectivenessofelectricityenergyefficiencyprogramsandsomeofitsdeterminants,
includingdecouplingmechanisms.Theresultsofthisstudysuggestthatdecoupling
mechanismsmaystrengthenthedemand‐reducingeffectofDSMspending.
Unfortunately,duemostlikelytoinsufficientdatafromdecoupledelectricutilities,
thesefindingswereinsignificant.
Thepresentstudyaimstobuildonthepreviousliteratureandthemethods
ofArimuraetal.(2011)tomorethoroughlyexploretherelationbetween
decouplingmechanismsandelectricitydemand.Itfirstmodelstheeconomic
incentivesbehindDSMinvestmentundertraditionalregulationandundera
decouplingmechanismandthenempiricallyanalyzestheeffectsofdecoupling
mechanismsonenergyconsumptionpercustomer.Thisstudydisregardsthe
potentialissueofendogeneityduetocorrelationofDSMspendingwithunexplained
demand,asArimuraetal.(2011)’sresultsdonotsuggestthatthisissueof
endogeneityexists.Finally,robustnesschecksareperformedontheresultsofthe
empiricalanalyses.
ModelingDSMInvestmentIncentives
Introduction
Thesituationinwhichtheregulatorsetsarequiredpriceorrevenueforthe
utilityandtheutilitydecideshowmuchandhoweffectivelytoinvestinDSM
programscanberepresentedasaprincipal‐agentgame.Theregulatoristhe
principal,andtheutilityistheagent.Asinallprincipal‐agentgames,theprincipal
hasanobjectivefunction,butdoesnothavealltheinformationitneedstobest
maximizethisfunction.Theagenthastheinformationnecessarytobettermaximize
thisfunction,butitactsonlyinitsownself‐interest.Duetothisasymmetric
information,theprincipalneedstheagentinordertoreachitsobjective,butitruns
theriskthattheagent’sobjectiveswilldifferfromtheoptimalattainmentofthe
principal’sobjective.Theregulatormustdesignthegameinsuchawaythatthe
incentivesofthetwopartiesalign.
24
Inthisgame,theregulator(principal)wantstomaximizeasocialwelfare
function,whiletheutility(agent)isonlyconcernedwithitsprofits.Theutilityhas
moreinformationthantheregulatordoesabouttheDSMoptionsavailableand
abouttheprojectedefficacyofeachoption.Theutilitycanusethisinformation
asymmetrytoincreaseitsprofitsbyactingstrategically.
Inasimpleversionofaprincipal‐agentgameonDSMprograminvestment
undertraditionalregulation,theregulatorwantstomaximizesocialwelfare.Social
welfareisdefinedastheintegralofdemand,ormarginalsocialbenefitofconsuming
oneunitofelectricity,lessthemarginalsocialcostofproducingandconsumingthat
electricity.Itisafunctionoftheexogenous,regulator‐determinedprice(p),quantity
ofelectricityconsumed(q),andthemarginalnetsocialbenefitelectricity
consumptionschedule.Itisassumedthatmarginalsocialcostofelectricity
consumptionisgreaterthanmarginalprivatecost,sincetheGHGemissions,air
pollution,andotherenvironmentalcostsassociatedwithelectricityarenot
internalizedintheprivatecostofelectricity.Forthesamereasons,itisalso
assumedthatthequantityofelectricityconsumedisabovetheefficientquantity.
Theregulator,therefore,wantstodecreasequantityofelectricitysoldby
encouragingDSMspending.Theregulatorcandosoby:
A. Requiring$XofDSMspending
B. Adjustingtherateofreturnoninvestmentviaaspecificprice(p)orrevenue
(R)basedontheutility’sreportedDSMspendinginthepreviousperiod
or
C. AdjustingtherateofreturnoninvestmentviaaspecificporRbasedon
perceivedDSMinvestmentefficacy.
Forthepurposeofthisexercise,itisassumedthattheregulatorcanchoose
oneoftwoallowedratesofreturn,ahighrewardrate(associatedwithpHorRH)and
alowpunishmentrate(associatedwithpLorRL).Strategy(B)assumesthatthe
rewardpriceissetiftheutilityinvestsatleast$XinDSMandthatthepunishment
25
priceissetotherwise.Strategy(C)assumesthattheregulatoruseselectricity
consumptioninthepreviousperiod(i.e.sincethelastratecase)todeterminewhich
p(orR)tosetinthecurrentperiod.Foranygivenperiod,theregulatorcantryto
encouragetheutilitytoinvestinDSMbypromisingtosetitspriceinafutureperiod
pt+1(orRt+1)asafunctionofestimateddemand‐reducingeffectofDSMinvestment
inthepreviousperiod.ThevalueofthisdemandreductionduetoDSMishenceforth
denotedEDSM.
Understrategy(C),whiletheregulatorcannotpreciselymeasuretheefficacy
ofaDSMprogramrelativetootherpotentialprograms,itcanestimatetheefficacy
byobservingenergyconsumptionpercapita.Theregulatorcanexaminemarket
trendsandrelevantfactorstoestimateprojectedconsumption,qp,tinthegiven
period.ItcannotconfidentlyattributechangesinrealizeddemandtoDSM
investmentorlackthereof;yetitknowsthatactualenergyconsumption(qa,t)equals
qp,t–EDSMt+ε t,whereε tcapturesunexpectedvariationandhasmeanzero.The
regulatorcan,therefore,setprice(pt+1)orrevenue(Rt+1)inthenextperiodasa
functionofqp,t‐qa,tsoastoalterprojectedrevenuesforperiodt+1asaresultof
actualquantityofelectricityconsumedinthepreviousperiod(dpt+1qt+1/dqa,t<0).
Forsimplicity,itisassumedthattheregulatordeterminesacutoffqc,,tsuchthatqc,,t
≤qc,,t.Foranygivenperiodt,theregulatorsetstherateaspH,torRH,tiftheprevious
periodresultedinaqa,t1≤qc,t1andsetstherateaspL,torRL,totherwise.Whenthe
regulatorchoosestosetprices,itsetstheratesbasedonprojectedrevenuesand
associatedquantities(qHandqLrespectively),suchthatpHqH>pLqL.Thus,the
regulatortakesthedemand‐reducingeffectofDSMintoaccountwhensettingthese
rates.
Thisisacrediblestrategyforsomerewardrate(pHorRH),punishmentrate
(pLorRL),andqcbecausetheprospectofincreasedfutureconsumersurplusdueto
decreasedconsumptionoutweighsthepotentialdecreaseinconsumersurplusasa
resultofahigherprice,forsomesufficiently‐largeconsumptionreductionandsome
sufficiently‐smallpriceincrease.Notethatthismodeldoesnotattempttouncover
thespecificvalueofX,therewardrate,thepunishmentrate,ortheqc.Itsimply
26
demonstratesthedifferencesineffectsofregulator‐orthirdparty‐imposedDSM
standardsandincentivesonutilityDSMinvestmentundertraditionalregulation
versusdecouplingmechanisms.
PartA–TraditionalRegulation
Undertraditionalregulation,theutility’sobjectivefunctionisdenoted:
Maxπ t=ptqt–ft–St
whereftisthefixedcostsassociatedwithsupplyingelectricitytothecurrent
customersandStistheamountthattheutilityspendsonDSMinperiodt.Notethat
thismodelassumesnomarginalcostsofelectricitydistribution.Foranygivenp,set
bytheregulator,theutilitywantstomaximizeq.Thefirstorderderivativeofthe
aboveequationwithrespecttoDSMspendingisthefollowing:
€
idπidS
= p idq
idS−1
withdqt/dSt≡EDSMt<0.
IftheregulatordoesnotinstituteanyrulesorincentivesconcerningDSM
andsetspricesexogenously,itisevidentfromtheaboveequationthattheutility
willmaximizeqandwillnotinvestinDSMatall.Iftheregulatorchoosesstrategy
(A)andrequirestheutilitytospend$XonDSM,theutilityhasanincentivetosteer
awayfromeffectiveDSMprograms.Theutilitywouldprefertoburnthemoneythan
spenditonDSM.Similarly,iftheregulatorchoosesstrategy(B)andbasespriceson
theamountofDSMspendinginthepreviousperiod,theutilityhasanincentiveto
spend$XonDSMifthepresentvalueofthebenefitsofdoingsoisgreaterthanthe
costs,butitwillchoosetodosoasineffectivelyaspossible.Iftheutilitycanspend
$XonDSMwithoutactuallyaffectingenergyconsumptionatall(dQ/dS=0),itwill
choosetodosoifδ(pHqH–pLqL)>Xwhereδ istheutility’sdiscountfactor(0≤δ≤1).
27
TheutilitymustbebribedorpunishedmoreiftheDSMspendingwereunavoidably
slightlyeffective.
Iftheregulatorusessignalsotherthanspendingtoestimatetheutility’s
effectiveinvestmentinDSMandsetspricesaccordingly(strategyC),theutilitywill
effectively3investanamount,X,inDSMinagivenperiodifthepresentvalueofthe
benefitsofthisinvestmentisgreaterthantheassociatedcost.Thisisrepresentedby
thefollowinginequality:
[θ1(pHqH)+(1θ1)(pLqL)–θ2(pLqL)–(1θ2)(pHqH)]*δ ≥X+pt*EDSM,t
whereθ1istheprobabilityoflowdemandbeingrealized(qa<qc)iftheutility
invests$XinDSM,θ2istheprobabilityofhighdemandbeingrealized(qa>qc)ifthe
utilitydoesnotinvestinDSM,,andptisthepriceinthecurrentperiod.
Assumingthattheexpectedvalueofqaisgreateriftheutilitydoesnotinvest
thanifitdoes,(i.e.θ1+θ2>1),thisinequalitycanberearrangedtothefollowing:
(pHqHpLqL)≥[X+ptEDSM,t]*[1/(δ(θ1+θ21))]
Theutilitywillonlyeffectivelyinvest$Xinenergyefficiencyifthe
punishmentpriceisassociatedwitharevenuesufficientlylessthantherevenue
associatedwiththerewardprice.Thesufficientdifferencedecreasesifthedirect
costoftheDSMinvestmentdecreases,ifthepriceinthecurrentperiodissmaller,if
theexpecteddemand‐reducingefficacyoftheinvestmentissmaller,iftheutility
valuesthefuturerelativelymore(δ isgreater),oriftheprobabilityofthedemand
realizationcorrectlyreflectingtheutility’sactionsisgreater(i.e.thevariabilityofε
islower).
3Forsimplicity,efficacyisconstrainedheretotakingonevalue(1)iftheinvestmentiseffectiveand0otherwise.
28
PartB–Decoupling
Underafulldecouplingmechanism,theregulatorchoosestheutility’s
requiredrevenue(R).TheutilitystillchooseswhethertoinvestinDSMandwhether
todosoeffectively.Inthiscase,however,theutility’sprofitisonlyafunctionof
requiredrevenues(andanychangesinfixedcosts).Anyshort‐termexcessor
shortageofrevenueisquicklyoffsetbypricetrue‐upsinthenextperiod.The
utility’sobjectivefunctionisrepresentedas:
Maxπ =Rf–S
Notethatquantityofenergysolddoesnotinfluencetheutility’sprofitsadverselyor
favorably(dR/dS=0).
WithnoregulationsorincentivesforDSMinvestment,thedecoupledutility
hasanincentivenottoinvestinDSM(dπ/dS=‐1).Iftheregulatorchoosesstrategy
(A)andrequirestheutilitytospend$XonDSM,theutilityisindifferenttoefficacy
oftheinvestment.Similarly,iftheregulatoroffersahigherallowedrevenueifthe
utilityspendsatleast$XinDSM(B),theutilitywilldosoifthepresentvalueofthe
benefitsoutweighsthecosts,δ(RHRL)>S,andwillagainbeindifferenttotheefficacy
oftheinvestment.Theutilityhasnoprivateincentivetoinvestmorethanthe
requiredamountineitherofthesecases.
Theregulatorcantrystrategy(C)andencouragetheutilitytoinvestinDSM
inarepeatedgamebysettingarequiredrevenueeachperiod,RHorRL(with
RH>RL),asafunctionofactualenergyconsumptionqainthepreviousperiod.The
utilitywillchoosetoefficientlyinvest$XinDSMifandonlyifthepresentvalueof
thebenefitsofinvesting$XinDSMoutweighthecosts.Inthecaseofadecoupled
utility,thissituationisrepresentedbythefollowinginequality:
[θ1(RH)+(1θ1)(RL)–θ2(RL)–(1θ2)(RH)]*δ ≥X
29
whereδ ,θ1,andθ2arespecifiedastheywereinpartA.Underadecoupling
mechanism,theutilityexperiencesnocostofdecreasedconsumptionduetoDSM
investment.AssumingtheexpectedvalueofqaisloweriftheutilityinvestsinDSM,
thesituationadherestotheaboveinequalityifandonlyif:
(RH–RL)≥X*[1/(δ(θ1+θ21))]
Theonlyfactorsthatdeterminewhetherornottheutilitywillinvest$Xin
DSMaretherelativeeffectsofdoingsoonfuturerevenues,theutility’sdiscount
factor,andtheprobabilityoftheregulatorcorrectlyassessingtheutility’sactions.
Onceagain,themoretheregulatorwantstheutilitytoinvestinDSM,thelargerthe
rewardrevenuemustberelativetothepunishmentrevenue.Thisrevenuedisparity
canbesmalleriftheutilityvaluesthefuturerelativelymoreorifthevarianceofεis
low.
Conclusions
ComparingParts(A)and(B)suggeststhefollowingconclusionsaboutthe
relativelevelsandefficaciesofDSMinvestmentunderdecouplingmechanismsand
traditionalregulationinthespecifiedscenarios:
1. Withnoregulatorincentivesorstandards,neitherdecouplednor
traditionallyregulatedutilitieswillinvestinDSM
2. WithregulatorstandardsonrequiredDSMspending,decoupledutilitieswill
investmoreeffectivelyinDSMthantraditionallyregulatedutilities
3. WithregulatorincentivesbasedonamountofDSMspendingonly,decoupled
utilitieswillbemorelikelytoinvestinDSMandwilldosomoreeffectively
thantraditionallyregulatedutilities
4. WithregulatorincentivesbasedonperceivedDSMinvestmentefficacyas
inferredfromenergydemand,decoupledutilitieswillproducemoreeffective
DSMinvestmentthantraditionallyregulatedutilities
30
Thefirstthreeconclusionshavebeenpreviouslydiscussed,butthefourthisnot
immediatelyapparent.Understrategy(C),theregulatormustofferalarger
reward/punishmentdiscrepancytoautilitythatisregulatedtraditionallythanit
mustoffertoadecoupledutilityinordertoencouragethesameamountofeffective
DSMinvestment.Thisisapparentbycomparingtheinequalitiesthatrepresentthe
sufficientconditionsforregularutilityinvestment$XinDSMundereachtypeof
regulation.SincepHqHisessentiallyanalogoustoallowedrevenues,RH,thesufficient
conditionis:
(RHRL)>[X+p0EDSM]*[1/(δ(θ1+θ21))]
undertraditionalregulation.Underafulldecouplingmechanism,thesufficient
conditionis:
(RHRL)≥X*[1/(δ(θ1+θ21))]
SincepHandEDSMtakeonlypositivevalues,itisevidentthat:
[X+p0EDSM]*[1/(δ(θ1+θ21))]>X*[1/(δ(θ1+θ21))]
Thus,thesufficientreward/punishmentstructuretoencourageDSMinvestmentof
$Xisgreaterundertraditionalregulationthanunderadecouplingmechanism.
Furthermore,itisreasonabletoassumethatincreasingRH‐RLiscostlyforthe
regulator,asitisboundedbyaminimumrevenuethatwillcausetheutilitytoshut
downandwouldcausedecreasedconsumersurplusduetohigherenergypriceson
theotherextreme.Asaresult,regulatorswillprobablynotofferreward/
punishmentstructuresthatincentivizecomparableDSMinvestmentsunderthetwo
typesofregulation.Thereward/punishmentstructureassociatedwiththe
decoupledutilitywillprobablyinducemoreDSMinvestment.Thus,utilitieswill
probablyinvestmoreinDSMunderdecouplingthanundertraditionalregulation.
31
Itisimportanttonotethatthismodelisnotaperfectrepresentationofthe
interactionsbetweenutilitiesandregulatorsconcerningDSMinvestment.
Furthermore,theseincentivemodelsonlycompareincentivesunderdecoupling
mechanismstothoseundertraditionalregulation.Utilitiesunderregulationtypes
thatareneithertraditionalregulationnordecouplingmechanismsmaypossess
differentincentivesthantraditionallyregulatedordecoupledutilities.Nonetheless,
thispapercautiouslyextendstheimplicationsofthismodeltoformhypotheses
abouthowdecouplingmechanismsaffectutilityDSMinvestmentsandelectricity
consumptioncomparedgenerallytoallotherutilities.
TheoryandMethods
HypothesestobeTested
ThepreviousmodelssuggestthattheeffectofdecouplingonDSMcanbe
brokendownintoatleasttwoeffects:itseffectonthelevelofDSMexpenditureand
itseffectontheefficacyofDSMexpenditure,givenafixedlevelofinvestment.
Accordingtothemodels,eachofthetwoeffectsshouldreduceenergyconsumption
ifdecouplingiscombinedwithDSMincentivesorenergy‐efficiencystandards.
Furthermore,underdecouplingmechanisms,reducedconsumptioninherently
affectsprice.Combiningthiswithdownward‐slopingdemandproducesathird
pathwaybywhichdecouplingandDSMreducedemand.
Therefore,thisstudyinvestigatesthehypothesisthatdecoupling
mechanismsdecreaseresidentialelectricityconsumption,butonlythroughtheir
effectonthelevel,directdemand‐reducingeffects,andindirectdemand‐reducing
effectsthroughpriceofDSMinvestment.Thishypothesisisrepresentedgraphically
32
below:
Specifically,totestthisoverallhypothesis,thispaperexploresthefollowing
subordinatehypotheses:
1.Decouplingmechanismsonlyaffectresidentialelectricity
consumptionandretailpricethroughtheireffectsonDSM
investment.
2.DecouplingmechanismsareassociatedwithincreasedutilityDSM
expenditure.
3.Decouplingmechanismsincreasethedirectdemand‐reducingeffectof
residentialDSMprograms.
4.DecouplingmechanismsincreasetheefficacyofDSMinvestment
throughtheindirecteffectofDSMonconsumptionthroughprice.
Analysesofthesesubordinatehypothesesallowforabetterunderstandingofthe
natureandpotentialmagnitudesoftheeffectsofdecouplingmechanismsonenergy
efficiency.Duetothelimitedtimeframeofthedata,onlyveryshort‐term
realizationsofthesehypothesescanbeanalyzedinthisstudy.Asdiscussedlater,
33
however,itisreasonabletobelieveveryshortruneffects(1‐4yrs)willindeed
translateintoslightlylonger‐termeffects(≈5‐10yrs).
DataandMethods
ThispaperbuildsonpreviousanalysesofenergyefficiencyandDSM
investmenttomodeltheeffectsofdecouplingmechanismsonelectricity
consumption.LoughranandKulick(2004)conductedatime‐seriescross‐
section/time‐seriesanalysisontheeffectofDSMinvestmentonelectricity
consumption,andArimuraetal.(2011)similarlymodeledthecost‐effectivenessof
electricityenergyefficiencyprograms.Contrarytothesepreviousstudies,the
presentpaperincludespost‐2006data4,recognizestheendogeneityissuesof
includingutility‐levelelectricitypricesasaright‐hand‐sidevariable,andincludesa
vectoroftimefixedeffectstobettercontrolfornationaltimetrendsandstructural
breaksinelectricityconsumption.
DuetodiscrepanciesinfrequencyofreportinginEIAforms,twoprimary
datasetswereassembledforthisanalysis:onewithmonthlyobservationsandone
withannualobservations.Theformerisusedforthemajorityoftheanalysis,while
thelatterisusedforanalyzingthesecondsubordinatehypothesis–theeffectof
decouplingmechanismsonlevelofDSMspending–only.Theentirestudyfocuses
ontheresidentialsectorandusesdatafromJanuary2001toDecember2010.
Forthemonthlydataset,dataonmonthlyelectricityconsumptionbysector
foreachUSelectricutilitywereretrievedfromtheEnergyInformation
Administrationdatabase(FormEIA‐826).Thesedatawerecombinedwithannual
customerdatabysectorforeachutility(FormEIA‐861)toobtainelectricity
consumptionpercustomerbysectorforeachutility.Utilitiesthatservecustomers
inmultiplestateswereseparatedintomultipleutilities,oneperstate,because
utilitydecouplingregulationlawsvarybystate.
Fourhundredfourutilities,eachwith50‐120monthlyobservations,were
includedintheanalysesonmonthlydata.Seventyutilitieswithfewerthan50
4ThevastmajorityofdecoupledUSutilitiesdidsopost‐2006.
34
monthsofdatawereexcludedfromthemonthlyanalysis.Extremeobservations,or
consumptionobservationsthatvariedfromthepriormonthbyafactoroffiveor
greaterwereexaminedandalteredorexcludedfromthedata,asappropriate.These
observationsarelikelyresultsofmergersoracquisitions,temporaryutility
shutdowns,humanerrorinreporting,ornaturaldisasterssuchashurricane
Katrina.Inthecaseofsupposedmergersoracquisitions,utilitieswerelabeledas
multiple,uniqueutilitiesbeforeandaftertheevent.Afewobservationsthat
portrayednegativesaleswerealsodiscardedfromtheanalysis.Intotal,eleven
observationswerediscardedduetonegativesalesorsuspicionofutilityshutdowns,
humanerror,ornaturaldisasters.
DSMspendingdataisonlyavailableontheannuallevelfromFormEIA‐861.
Therefore,anannualdatasetwascreatedtoanalyzeDSMspending.Inthisanalysis,
utilitieswithfewerthanfiveyearsofdatawerediscarded.Datafromutilitiesthat
residedinmultiplestateswerealsoexcludedfromtheanalysissincedistinguishing
betweenspendingineachstatewasnotfeasiblefortheseutilities.Itisnotablethat
manyutilitiesarecompletelyexcludedfromFormEIA‐861.Only161utilitiesand
1,502annualobservationswereincludedinthispartoftheanalysis,primarilydue
tolackofDSMspendingdata.
Somethird‐partyDSMspendingthroughutilitiesisalsoreportedbyutilities
onEIAForm861.Asshownintheliterature,thisisreasonable,astheexistenceofa
decouplingmechanismaffectsathird‐partyenergyefficiencyprovider‘sabilityto
effectivelyinvestinDSM(Lazer,Weston,andShirley2011).Theinclusionof
ratepayer‐funded“third‐party”DSMspendingreducesbiasresultingfromthe
geographicalheterogeneityinstructureandexistenceofregulatoryinstitutions
responsibleforpromotingDSM.
Thispaperreplicatesmanyofthecontrolvariablesandusesseveralofthe
datasourcesfrompreviousstudies.Asadeparturefromsomeoftheprevious
35
literature,thispapercontrolsfortheexistenceofastateenergyefficiencyresource
standard(EERS),statequarterlypersonalincome,andtimefixedeffects.5
OLSand2SLScross‐section/time‐seriesanalysesareusedtoinvestigatethe
statedhypotheses.First,theeffectofadecouplingmechanismonresidential,per‐
customerelectricityconsumptionisfirstestimatedusingthefollowingOLSmodel:
Equation1:
Electusmt=B0+B1Decouplingusmt+B2Res.Customersust+B3NatGasPricesmt+
B4FuelOilPricemt+B5GDPst+B6Popst+B7Incomest+B8EERSst+
B9EnvSensitivityst+B10CDDsmt+B11HDDsmt+αu+γsm+εusmt
whereElect=thenaturallogarithmofresidential,per‐customerelectricity
consumption,EERS=adummyvariableforwhetherornotthestatehadanEnergy
EfficiencyResourceStandardinplace,EnvSensitivity=anstateenvironmental
sensitivitymeasure,CDD=coolingdegreedays,HDD=heatingdegreedays,u=
utility,s=state,m=month,andt=year.αandγarevectorsofutility‐levelandtime
fixedeffects,respectively.SeeAppendixBforfulldescriptionsofthevariables.The
naturallogarithmofresidentialelectricityconsumptionisusedasadependent
variabletocapturepercentage,asopposedtoabsolute,changesinconsumption.
Byincludingavectorofutility‐levelfixedeffects,oradummyindicator
variableforeachutility,theanalysiscontrolsforallsystematicdifferencesbetween
utilities,suchassize,thatdonotvarywithinthedecade.Theinclusionofavectorof
timefixedeffectsnormalizesoutanynationwidetimetrendsandtime‐specific
changesthatwouldaffectthedependentvariable.Utilitycustomerbaseandstate‐
andtime‐specificindicatorsofweather,economicgrowth,populationgrowth,
5IncontrasttoArimuraetal.’sstudy,thispaperdoesnotattempttomodeltherelationbetweenbuildingcodes,housingstarts,andenergyconsumption.Arimuraetal.neglecttoaccountforthetimelaginimportanceofbuildingcodes.Withoutamechanismtocapturethiscomplicatedrelation,thesevariablesseemtopickupotherpoliticalandenvironmentalsensitivityfactorsandmayactuallyconfoundresults.
36
income,environmentalstandards,anddemonstratedenvironmentalconcernare
exogenouscontrolvariables.Withallofthesecontrols,theonlyremainingvariation
fortheexistenceofdecouplingandotherpotentialomittedvariablestoexplainis
utility‐specificchangesinconsumptionpercustomerovertimethatarenotaresult
ofchangesinsizeofthecustomersbase.
Thefullmodeloftheeffectofdecouplingmechanismsonresidential,per‐
customerelectricityconsumptionincludesDSMspendingandaninteraction
betweenDSMspendingandthedecouplingdummyvariable.This2SLSmodelalso
controlsforaninstrumentedutility‐levelretailelectricityprice:
Equation2:
Electusmt=B0+B1Decouplingusmt+B2Res.Customersust+B3ElectricityPricemt+
B4NatGasPricesmt+B5FuelOilPricemt+B6GDPst+B7Popst+B8Incomest
+B9EERSst+B10EnvSensitivityst+B11CDDsmt+B12HDDsmt+B13DSMust+
B14DecouplingxDSMusmt+αu+γsm+εusmt
withalltermsdefinedastheywereinthepreviousmodel.IntheRobustnessTests
section,thisstudyexploresthepotentialissueofendogeneityofdecouplinginthis
equation.
DespitetheresearchofJaffeandStavins(1995)regardingthelingering
effectsofDSMinvestmentonconsumption,thisanalysisfindsthatalinear
relationshipbetweenthelogarithmsofthisyear’sDSMinvestmentand
consumptionisthebest‐fittingmodeloftherelationbetweenrecentDSM
investmentandthisyear’sconsumption.LaggedvaluesofDSMinvestmentarenot
significant.
Toaddresstheendogeneityofelectricitypricethrough2SLS,2005state‐
leveldataonthepercentofelectricitygenerationfromoil,naturalgas,andcoalare
interactedwithmonthlycitygate(wholesale)naturalgasprice,monthlyUSoil
refinercosts,andtheaverageannualpriceofcoal,respectively.State‐levelpercent
37
generationfromrenewablesourcesisalsointeractedwithUScoalprice6.Thereis
noreasontobelievethatthesevariableswouldimpactelectricitydemandexcept
throughtheireffectonelectricitypriceandpotentiallythroughtheireffectonretail
naturalgasprice.Atestofjointsignificanceonthecoefficientsoftheseinstruments
inthefirst‐stageregressionproducesanF‐statisticof45.8,whichisassociatedwith
ap‐valueoflessthan.0001.Thisconfirmsthevalidityoftheseinstruments.
Thefollowingcross‐section/time‐seriesmodeloftotalutilityannualDSM
spendingperresidentialcustomerisusedtoexploretheeffectofdecouplingon
levelofDSMspending:
Equation3:
DSMust=B0+B1Decouplingust+B2Res.Customersust+B3GDPst+B4Popst+B5Incomest
+B6EERSst+B7EnvSensitivityst+B8CDDst+B9HDDst+αu+γt+εust
whereDSM=thenaturallogarithmofannualDSMspending,u=utility,s=state,
andt=year.αandγarevectorsofutility‐levelandtimefixedeffects,respectively.
Standarderrors,clusteredonutility,wereusedinallregressionstoaccount
forheteroskedasticityandautocorrelation.Evenwhenavectoroftimefixedeffects
isincluded,aWoodridgetestforautocorrelationinpaneldatageneratedan
F(1,403)statisticof355,whichisassociatedwithalessthan.1%chancethatthe
datadoesnotsufferfromautocorrelation.Theclusteredstandarderrorsaremuch
morerobusttoissuesofautocorrelationandheteroskedasticitythanthetraditional
standarderrors.Thetrueautocorrelationstructureofthedatacouldnotbe
captured,sothisapproachisthebestavailableoption.Notethatthepresenceof
autocorrelationsolelyaffectsthepredictedstandarderrorsofpointestimates,while
inaccurateeffortstocapturetheautocorrelationstructurewouldcauseendogeneity
issuesandbiasthepointestimates.6Interactiontermsbetweenpercentrenewablegenerationandotherfuelpricesaswellastheinteractionbetweenmonthlyuraniumpriceandpercentgenerationfromnuclearenergywereexcludedbecausetheywerefoundtobeirrelevantinthefirststage.
38
Results
OverallEffectsofDecouplingonConsumptionandPrice
Consistentwithsubordinatehypothesis#1,thissectionshowsthat
decouplingmechanismsarecorrelatedwithelectricityconsumptionandpriceonly
throughtheirrelationwithDSMinvestment.Thesefindingsarerobusttoexclusion
oftheenvironmentalsensitivityindicatorvariableandthedummyvariableof
existenceofastateenergyefficiencyresourcestandard.
Thefirstmodel(Equation1)includesdecouplingbutnotprice,DSMorits
interactionwithDSM.Thus,thecoefficientondecouplinginthismodelcanbe
understoodasthefulleffectofDSMthroughitsvariouschannels.AsColumn1of
Table1indicates(SeeAppendixA),thecoefficientofdecoupling(B1)inthismodelis
‐.05.Thiscoefficientrepresentsthedifferenceintheexpectedmeansofthenatural
logarithmofconsumptionbetweendecoupledutilitiesandnon‐decoupledutilities.
Alternatively,theratioofthemeanofconsumptionfordecoupledutilitiesovernon‐
decoupledutilitiesise‐.05,orabout.95.Allelseequal,ifautilityswitchestohavinga
decouplingmechanismfromhavingnone,expectedresidential,per‐customer
electricityconsumptiondecreasesbyabout5%.Thesignofthisresultissignificant
atthe2%levelforatestofthenullhypothesisthatdecouplingmechanismshasno
effectonresidentialelectricityconsumption.
Whentheeffectsofdecouplingonconsumptionworkingthroughpriceand
DSMinvestmentareeliminated,however,thissignificancedisappears.Totestthe
effectsofeliminatingthesepotentialcausalavenues,Equation2(Column2Table1–
AppendixA)addsascontrolsresidentialelectricityprice,utilitylogannualDSM
spending,andaninteractiontermofDSMspendingandadummyforadecoupling
mechanismtothemodeldescribedbyEquation1.Becauseelectricitypricemaybe
endogenous,thisequationwasestimatedwith2SLS.Thefirststageregressionis
giveninColumn1ofTable3(AppendixA).
Withtheinclusionofthesevariables,thecoefficientonthedecoupling
dummyshrinksto‐.007andisnotsignificantlydifferentfromzero.Sincethemodel
39
controlsforlevelofDSMinvestmentandfortheincreaseddemand‐reducingeffects
ofDSMinvestmentassociatedwithdecoupledutilities,thiscoefficientestimatesthe
effectofdecouplingmechanismsnotrelatedtoDSMinvestmentorpriceon
electricitydemand.FordecoupledutilitiesthatdonotparticipateinanyDSM
investment,themodelfindsnosignificanteffectofhavingdecoupledonelectricity
consumption.
Thisresultisrobusttoexclusionoftheenvironmentalsensitivityrating
variableandthevariableforexistenceofanenergyefficiencyresourcestandard
(Column3Table1).Becauseenvironmentalsensitivityratingsandtheexistenceof
anenergyefficiencyresourcestandardarecorrelatedwiththepresenceofa
decouplingmechanism(r=.26and.30,respectively),onemightbeconcernedwith
thepresenceofthesecontrolsinthemodel.Whenthesevariablesareexcludedfrom
theanalysis,decouplingstillshowsnosignificantrelationtoconsumptionother
thanthroughitseffectonDSMinvestmentandprice.Thepointestimateand95%
confidenceintervalontheisolateddecouplingcoefficientbarelychange.
Consistentwiththeliteratureandcontrarytothefearofmanyopponentsof
decoupling,decouplingmechanismsalonedonotappeartoinherentlysignificantly
increaseprices.Column2ofTable3rerunsthefirststageanalysiswithoutthe
variablesofDSMinvestmentanditsinteractionwithdecoupling.Withoutholding
thesevariablesconstant,decouplingdoesappeartoincreaseprices.Specifically,
decouplingisassociatedwitha1%increaseinpricewhenDSMinvestmentis
ignored,andthisrelationissignificantatthe10%level.
IftheeffectsofDSMinvestmentareproperlyaccountedfor,however,these
resultsdisappear(Column1Table3–AppendixA).HoldingDSMinvestment
constant,ifautilityhasadecouplingmechanismbutnoDSMinvestment,the
decouplingmechanismispredictedtohavenosignificanteffectonprice.The
coefficientondecouplingis.004andisnotsignificantatanyconventionallevel.This
insignificanceremainswhentheenvironmentalsensitivityandEERScontrol
variablesareexcluded(Column3–Table3).Therefore,thisstudyconcludesthat
decouplingmechanismsonlyaffectpricethroughtheireffectonDSMspending.
40
Thestrikingdifferenceinmagnitudeandsignificanceofthecoefficient
associatedwithdecouplingbetweenmodelsofelectricityconsumptionthatinclude
DSMspendingandthosethatdonotisexploredinthefollowingsections.
EffectofDecouplingMechanismsonLevelofDSMSpending
Toprovidemoreinsightintotherelationbetweendecouplingmechanisms
andelectricityconsumption,thisstudyanalyzesthreepotentialimpactsthat
decouplingmechanismsmayhaveonDSMinvestment.Thissectioninvestigatesthe
secondsubordinatehypothesis:theeffectofdecouplingmechanismsonthelevelof
DSMspending.Contrarytothehypothesis,anestimateoftheOLSmodelofDSM
spendingoutlinedinEquation3(Column1Table2–AppendixA)suggeststhat
decouplingandlevelofDSMspendingarenotsignificantlycorrelated.
BecauseitisimpossibletoengageinnegativeDSMspendingandbecause
therearemanyutilitieswith$0DSMspending,atobitmodelmaybemore
appropriatethananOLSmodelinthisinstance.Evenwiththismodelspecification,
however,thecoefficientondecouplingisnotstatisticallydifferentthanzero
(Column2Table2–AppendixA).Thisprovidesfurtherevidencethatdecoupling
mechanismsandlevelofDSMspendingareuncorrelated.
Itisimportant,however,toconsiderthedistributionofDSMspending.The
distributionisnotnormalandhasaskewnessof6.99.Therearemanyobservations
withzeroorverylowvaluesofDSMspendingandafewobservationswithvery
extremehighvalues.Toavoidassuminganormaldistributionandtolimitthe
effectsofoutliers,aquantileregressionwasused.Theresultsofthismodelshowa
positiveeffectofdecouplingonlevelofutilityDSMinvestmentthatissignificantat
the10%level(Column2Table2‐AppendixA).Thisregressionsuggeststhat
decouplingdoesencouragehigherutilityDSMspendingandthatthenormal
distributionalassumptionmayhavecausedinaccurateestimatesintheOLSand
tobitmodels.Thequantilemodelestimatesthat,allelseequal,thepossessionofa
decouplingmechanismincreasesautility’spredictedDSMspendingby41%.
41
Becauseofthefailureofthequantilemodeltocontrolforheteroskedasticity
andautocorrelation7,however,cautionshouldbeexercisedwheninterpretingthe
significanceoftheseresults.Furthermore,recallthatsinceDSMinvestmentdatais
onlyavailableannually,thisanalysishasfarfewerobservationsthantheanalysisof
Equation1.Astheremaybesomebiasduetotherelativelysmallsamplesizeofthis
dataset,thisisanotherreasonthatthepointestimategivenbythismodelshouldbe
treatedwithcaution.
EffectofDecouplingMechanismsontheDirectDemandReducingEffectsofDSM
Spending
Thethirdsubordinatehypothesisinthispaperisthat,controllingforthe
levelofDSMinvestment,decouplingmechanismsincreasethedemand‐reducing
effectsofDSMspending.Totestthishypothesis,the2SLSmodelofEquation2
(Column2Table1–AppendixA)isagainused.ThismodelcontrolsforlevelofDSM
investmentandfortheinteractionbetweendecouplingandDSMinvestment.The
coefficientonthisinteractiontermrepresentstheincreaseinefficacyofDSM
investmentassociatedwithdecouplingmechanisms.Thiscoefficientisestimatedto
be‐.004andissignificantatthe5%level.Thissupportsthehypothesisthat
decouplingmechanismsincreasedemand‐reducingeffectofutilityDSMinvestment
foragivenlevelofinvestment.GivenafixedlevelofinitialDSMinvestment,this
modelestimatesthata10%increaseinDSMinvestmentofadecoupledutility
decreasesestimatedresidential,per‐customerelectricityconsumptionby.04%
morethana10%increaseinDSMinvestmentofanon‐decoupledutilitywould
decreaseestimatedconsumption.
7Duetoinsufficientobservationsclusteredstandarderrorscouldnotbecomputedinthispartoftheanalysis.
42
EffectofDecouplingMechanismsontheEfficacyofDSMInvestmentduetoitsIndirect
EffectonConsumptionThroughPrice
Besidesincreasingthedemand‐reducingeffectsofDSMinvestment,
decouplingmechanismsmayalsoincreasetheefficacyofDSMinvestmentat
reducingconsumptionthroughtheeffectofDSMinvestmentonprice.Inutilities
withdecoupling,DSMinvestmentispredictedtoincreaseprices,andhigherprices
arepredictedtodecreaseconsumption(Hypothesis4).Thissectionexploresthis
subordinatehypothesisbyconsideringtheestimationoftheeffectofDSM
investmentofdecoupledutilitiesonprice,contrastingthiseffectwiththatofnon‐
decoupledutilitiesthatinvestinDSM,andverifyingthepredictedeffectofincreased
pricesonconsumption.
Aspredicted,resultssuggestthatDSMinvestmentincreasesresidential
electricitypriceunderdecouplingmechanismsandhasnoeffectonpriceunder
othertypesofregulation.Inthefirststageofthe2SLSmodeldepictedinEquation2,
thecoefficientonthevariabledepictingDSMinvestmentisessentiallyzeroand
associatedwithat‐statisticof.17(Column1Table3–AppendixA).Thisindicates
that,fornon‐decoupledutilities,DSMinvestmentdoesnotsignificantlyaffectprice.
Amongonlydecoupledutilities,however,theredoesappeartobeapositiverelation
betweenDSMinvestmentandprice.Theinteractiontermbetweendecouplingand
DSMinvestment(Column1Table3–AppendixA)ispositiveandsignificantatthe
10%level.ThisweaklysupportsthehypothesisthatDSMinvestmentincreases
residentialelectricityprice,atleastintheshortrun,underdecouplingmechanisms.
Consistentwitheconomictheory,thisstudyalsofindsevidencethathigher
pricesdecreaseelectricitydemand.Thecoefficientonpriceinthesecondstageof
this2SLSmodelis‐1.47,whichisstatisticallysignificantatthe.001level(Column2
Table1–AppendixA).Apriceincreaseof$.01/kWhisassociatedwitha1.5%
decreaseindemand.Atameanpriceofabout$.10/kWh,thisimpliesaprice
elasticityofabout.15,whichiswithinthe‐2.001to‐.004range(median=‐.28)of
recentpriceelasticityestimatesofshortrundemandintheliterature(Espeyand
Espey2004).
43
RobustnessTests
ThissectionaddressessomepotentialconcernsabouttheestimatesinTable
1.Itfirstteststhesensitivityoftheresultstoincludingamonthlyratherthanannual
coalpriceasaninstrumentalvariabletopredictelectricityretailprice.Itthen
exploreswhetherthecorrelationbetweenpossessionofadecouplingmechanisms
andelectricityconsumptionispartiallyduetothecontinuationofpre‐existing
trends.Finally,thissectionusesprobitanalysistoexplorethepossibilitythat
electricityconsumptionaffectsautility’sdecisiontodecoupleanddiscussesthe
potentialbiascausedbythepresenceofthisendogeneityissue.
UseofanAnnualInstrumentalVariable
Somereadersmayfindtheuseofannualcoalpriceasopposedtomonthly
coalpriceasaninstrumentformonthlyelectricitypricetroubling.Specifically,they
mayworrythattheuseofareplicatedannualvariablemightartificiallyincreasethe
power,ortheperceivedrelevance,oftheinstruments.MonthlyUScoalpriceswere
notavailable.TochecktherobustnessoftheannualUScoalpriceestimate,models
wereestimatedusingamonthlycoalpriceindex,Australianthermalcoal,inplaceof
annualUScoalprice.ThismonthlyindexisfoundtobehighlycorrelatedwithUS
coalprice,butitisfoundtobeaninferiorinstrumentbecauseitisslightlyless
powerfulinexplainingUSretailelectricityprices.
Thereplacementdoesnotaltertherejectionofthenullhypothesisthatthe
instrumentsarerelevant.Itdoeslowerthe95%intervalforthesecondstageeffects
ofa$.01increaseelectricityretailpriceonelectricityconsumption,fromadecrease
ofbetween.6%and2.3%toadecreaseofbetween.2%and1.7%.Whenbothcoal
priceindicatorsareincluded,theeffectoftheAustraliancoalpriceindexon
residentialelectricitypricelosessignificance,andthe95%confidenceintervalof
thedecreaseinconsumptionassociatedwitha$.01priceincreasebecomes.4%to
.9%.Whilethedifferencesintheseintervalsarenontrivial,theoverlapofthe
confidenceintervalsisnotable.Furthermore,theuseofthemonthlyindicator
44
variableinsteadoftheannualUSpricevariablehasanegligibleeffectonthepoint
estimatesandsignificanceoftheotherexogenousvariables.Thisprovidesevidence
forrobustnessoftheanalysesinthisstudytoatheoreticalchangeinannualversus
monthlyUScoalprice.
PreExistingTrends
Becauseofthetime‐seriesnatureofthedata,itisimportanttoconsiderthe
possibilitythatpercustomerelectricityconsumptionwasdecreasingpre‐
decouplingfortheutilitiesthatlaterdecoupled.Becausealloftheutilitiesinthe
datasetthatdecoupledbetweentheyearsof2001and2010didsoafter2005,pre‐
existingtrendscanbecapturedbyanalyzingdatafrom2001‐2005.Utilitiesthat
adopteddecouplingmechanismspriorto2001wereexcludedfromthispartofthe
analysis.
Column4ofTable1(SeeAppendixA)showstheestimationofamodelusing
only2001‐2005dataofresidentialper‐customerelectricityconsumptiononayear
trend,aninteractiontermbetweenayeartimetrend8andwhethertheutility
decoupledbetween2006and2010,controlvariables,andutility‐fixedeffects.The
interactiontimetrendshouldcaptureanysystematicdifferencesinenergyuse
trendsbetweenutilitiesthatlateradopteddecouplingmechanismsandthosethat
didnotdoso.Ifper‐customerenergyconsumptiondecreasedrelativelymoreor
increasedrelativelylessinutilitiesthatlaterdecoupled,thecoefficientofthis
variableshouldbenegative.Infact,asseeninColumn4ofTable1,thecoefficientof
thisinteractiontermisactuallypositiveandsignificantatthe1%level.Controlling
forthevariablesinthepreviousmodel,pre‐2006energyconsumptionwasactually
increasingmoreforutilitiesthatdecoupledduring2006‐2010thanforutilitiesthat
didnotdecoupleduringthistimeperiod.Thus,theperceivedeffectsofdecoupling
mechanismsreducingenergyconsumptiondonotseemtosimplybethe
continuationofpre‐existingutility‐specifictrends.
8Note–thisyeartimetrendisnotusedinmodelswithtimefixedeffectsduetoitsinsignificance.
45
PotentialEndogeneityoftheDecouplingVariable
Theupwardtrendinconsumptionforutilitiesthatlaterdecoupledsuggests
thatincreasesindemandmighthavecausedtheadoptionofdecoupling
mechanisms.Inresponsetothisconcern,thisstudyusesprobitanalysisto
investigatewhatcausesutilitiestodecouple.Column1ofTable4(AppendixA)
showstheresultsofamodelthatpredictswhetherautilitydecoupledbetween
2006and2010asafunctionofJanuary2001valuesofvariousindependent
variablesforthe384utilitieswhohadnotdecoupledby2006.Theseresultsindicate
thatutilitieswithalotofcustomerswhoeachusealotofenergythatarelocatedin
wealthy,environmentally‐consciousstatesaremostlikelytodecouple.Controlling
fortheseJanuary2001characteristics,theresultsinColumn2ofTable4estimate
howtrendsinvariablesbetweenJanuary2001andDecember2005affected
utilities’decisionstodecouple.Theseresultssuggestthattheonly2001‐2005trend
thatissignificantinpredictingdecouplingadoptionwastheinstitutionofastate
energyefficiencyresourcestandard.
Furthermore,thet‐statisticassociatedwiththeincreaseinenergyuseper
customerisabout1,whichsuggeststhat,ifanything,growingenergyuseper
customermayalsoincreasethechancesofautilitydecoupling,althoughthis
relationisnotstatisticallysignificant.Thisfindingisnotsimplydueto
multicollinearitybetweentrendvariables.Thesignandtheinsignificanceofthe
coefficientpersistswhenpercustomerconsumptionistheonlytimetrendincluded
(Column3Table4–AppendixA).
Theresultsoftheprobitmodelssuggestthatthedecouplingdummyvariable
mayormaynotbeendogenousintheper‐customerelectricityconsumptionmodels.
Thefactthatutilitieswithhighper‐customerconsumptiontendtoadoptdecoupling
mechanismsshouldnotcauseendogeneityissuesbecauseutility‐fixedeffectsare
46
includedintheconsumptionmodels.9Incontrast,thesuggestionthattrendsinper‐
customerconsumptionmayaffectautility’sdecisiontodecouple,albeitstatistically
insignificant,provokesconcernaboutpotentialendogeneityissuesinthemodelsof
electricityconsumptionofTable1.Ifthiscausalrelationdoesexist,however,the
resultsoftheTable4probitmodelssuggestthatincreasingper‐customerelectricity
consumptionincreasesthechancesofautilityhavingadecouplingmechanism.This
impliesthatendogeneitywouldbiasthecoefficientofthedecouplingvariableinthe
positivedirection.Thus,thecoefficientsofdecouplingintheelectricityconsumption
modelsareeitherunbiasedorclosertozerothanthetruecoefficient.Thisfurther
strengthenstheargumentthatdecouplingmechanismsreduceper‐customer
residentialelectricityconsumption.
LongRunImplications
Thefindingsinthispaperrepresentshortrunrelationships(<5years)
betweendecouplingmechanismsandefficiencyofresidentialelectricity
consumption.Thereissomereasontobelievethattheserelationshipspersist,in
somemagnitude,foranextendedperiodoftime.AsJaffeandStavins(1995)found,
DSMinvestmentsaffectenergyconsumptionforyears.
ThefindingthatDSMinvestmentofutilitieswithdecouplingmechanisms
causeshigherprices(andthathigherpricesimpactdemand),however,isinnatelya
shortrunresult.ThelinkbetweenDSMinvestmentsofdecoupledutilitiesandprice
isthat,underadecouplingmechanism,reduceddemandwillcausepricetoincrease
withthenextscheduledtrue‐up.Onceanewratecaseoccurs,however,new
revenuetargetsandcorrespondingpricesaresetbyaregulatorandareless
dependentonpreviousconsumption.Decreasedconsumptionitselfmayormaynot
affecttheregulator’spricedecision.Thus,increaseinpricemayonlypersistuntil
thenextratecase(≈3‐6yrs).
9Theerrorterminthesemodelsonlycapturesutilityandtime‐specificchangesinconsumptionandwouldnot,therefore,becorrelatedwithdifferencesinabaselinemonth’sper‐customerelectricityconsumptionacrossutilities.
47
Nonetheless,eveniftheregulatordecidestorestorepricestotheirpre‐true‐
uplevels,consumptionisunlikelytoreturntothe“efficient”marketlevelatthis
price.Energyefficiencyinvestmentsandbehaviorchangescausehysteresis,or
history‐dependent,effects.Ifendusersrespondtohighelectricitypricesbybuying
energyefficientappliancesormakingbehavioralchangestowastelessenergy,
lowerenergypricesmaynotcausethemtogetridoftheirnew,efficientappliances
ortochoosetoswitchbacktowastefulbehaviors.Therefore,theeffectondemand
ofhigherpricesduringtrue‐upsmayverylikelypersistthroughsubsequentrate
cases.
Conclusions
Withwidespreadconcernaboutglobalclimatechangeandenergysecurity,
theefficacyofmechanismstoimproveenergyefficiencyisofconsiderableinterest.
Recentliteratureonthedeterminantsofenergyinefficiency,includingconsumer
choicefailureandutilitythroughputincentives,hasespeciallyincreasedinterestin
promotingutilityinvolvementinDSM.Decouplingmechanismsareanincreasingly
populartechniquetoencourageutilityinvolvementinenergyefficiencyissues,but
littleempiricalanalysishadbeenconductedintotheeffectsanddeterminantsof
decouplingmechanismsonelectricitydemand.Thispaperexploresthisrelation
usingrecentutility‐leveldata.
ModelsoftheinterplaybetweenutilityDSMinvestmentandregulator
incentiveshaveimportantimplicationsontheexpectedeffectsofdecoupling
mechanismsonenergyefficiency.Thesemodelsindicatethatdecoupling
mechanismsonlyaffectinvestmentinDSMinvestmentifadditionalDSMstandards
orincentivesexist.Moreover,inthepresenceofstandardsonDSMspending,
decoupledutilitieswillinvestmoreeffectivelyinDSMthantraditionallyregulated
utilities.Similarly,inthepresenceofincentivesbasedonlyonlevelofDSM
spending,decoupledutilitieswillbemorelikelytoinvestinDSMandwilldoso
moreeffectivelythantraditionallyregulatedutilities.Finally,withregulator
incentivesbasedonperceivedDSMinvestmentefficacy,asinferredfromenergy
48
demand,decoupledutilitieswillproducemoreeffectiveDSMinvestmentthan
traditionallyregulatedutilities
Basedonthesemodels,thispaperexploresthehypothesesthatdecoupling
mechanismsdecreaseresidentialelectricitydemandandthatthisisaccomplished
throughencouragingagreaterlevelofDSMinvestment,alargerdemand‐reducing
effectofanygivenlevelDSMinvestment,andapriceincreasethatfurther
discouragesconsumption.Thispapertheorizesthattheeffectofdecoupling
mechanismsisprimarilyduetoitseffectsonutilityDSMinvestmentanditseffects
onpricethroughDSMinvestment.
Consistentwiththehypotheses,empiricalresultssuggestthatdecoupling
mechanismsarecorrelatedwithelectricityconsumptionandpriceonlythrough
theirrelationwithDSMinvestment.NotcontrollingfortheeffectsofpriceandDSM
investment,pointestimatesofthedecreaseinconsumptionassociatedwith
decouplingmechanismsarequitelargeandsignificantatthe5%level.Whenthe
effectsofdecouplingonconsumptionworkingthroughpriceandDSMinvestment
areeliminated,however,thissignificancedisappears.
Asaresultofasmallsamplesize,thispaperneitheraffirmsnorrejectsthe
hypothesisthatdecouplingmechanismsincreasethelevelofutilityDSMspending.
ThelackofsignificanceinOLSandtobitmodelssuggeststhatdecoupling
mechanismsarenotcorrelatedwithlevelofDSMinvestment.However,theresults
ofaquantileregression,whichaccountsfortheskeweddistributionofDSM
spending,doessuggestthatdecouplingmechanismsmayindeedincreaselevelof
DSMspeding.Moreresearchisneededtothoroughlyexplorethishypothesis.
GivenafixedlevelofDSMspending,resultsstronglysuggestthatdecoupling
mechanismsincreasethedirectdemand‐reducingeffectsofDSMspending.Alarge
estimatedeffectofincreasedDSMinvestmentofdecoupledutilitiesrelativetothat
ofotherutilitiesisfoundtobesignificantatthe5%level.Thissubstantiatesthe
resultofthetheoreticalmodelconcerningefficacyofDSMinvestment.Specifically,
themodelindicatesthatDSMinvestmentofdecoupledutilitiesismoreeffective
thanthatoftraditionally‐regulatedutilitieswhenregulatorsdesignDSMinvestment
49
incentivemechanismsandregulationsthatarebasedprimarilyonlevelofDSM
spending.
Thispaperalsofindsweakevidencethatdecouplingmechanismsincrease
theefficacyofDSMinvestmentinreducingconsumptionthroughtheeffectofDSM
investmentonprice.DSMinvestmentbydecoupledutilitiesissignificantly
negativelycorrelatedwithpriceatthe10%level.Higherpriceswerealsofoundto
beveryhighlycorrelatedwithdecreasedelectricitydemand.
Testsonpre‐2006datademonstratethattheperceivedeffectofdecoupling
mechanismsonelectricityconsumptionisnotduetothecontinuationofpre‐
existingutility‐specifictrendsinelectricityconsumption.Probitanalysessuggest
thatthedecouplingdummyvariablemayormaynotbeendogenousintheper‐
customerelectricityconsumptionmodels.However,thesignofthepointestimates
oftherelationbetweendecouplingandDSMsuggeststhat,ifanything,thetrue
impactofdecouplingonelectricityconsumptionisactuallymorenegativethan
estimatedinthispaper.Thisstrengthenstheargumentthatdecouplingmechanisms
reduceper‐customerresidentialelectricityconsumption.
Whileitisreasonablyclearthatdecouplingmechanismspromotemore
efficientelectricityuseintheresidentialsectorthroughmoreeffectiveutilityDSM
investment,thelinkbetweendecouplingmechanismsandlevelofDSMexpenditure
remainsrelativelyambiguous.CollectingDSMspendingdataformoreutilities
wouldimprovetheestimationoftheeffectofdecouplingmechanismsonlevelof
DSMspending.Morein‐depthresearchofthedeterminantsofDSMinvestmentand
thespecificregulatorpoliciesconcerningDSMinvestmentwouldalsoassistin
understandingtheinterplaybetweenincentivestructure,levelofDSMinvestment,
andefficacyofDSMinvestment.Withthisadditionalresearchwillcomeaneven
greaterunderstandingoftheeffectsofdecouplingmechanismsonenergyefficiency.
50
References
ACEEE(AmericanCouncilforanEnergy‐EfficientEconomy)(2011).“StateEnergyEfficientPolicyDatabase”.AmericanCouncilforanEnergy‐EfficientEconomy.Availableat:http://www.aceee.org/sector/state‐policy
Ackerman,FrankandElizabethA.Stanton(2008).“WhatWe’llPayifGlobal
WarmingContinuesUnchecked.”NaturalResourceDefenseCouncilReportMay2008.Availableat:http://www.nrdc.org/globalwarming/cost/cost.pdf
AGA(AmericanGasAssociation)(2007).“UpdateonRevenueDecoupling
Mechanisms.”NaturalGasRateRound‐UpApril2007.Availableat:www.epa.state.il.us/air/climatechange/documents/subgroups/power‐energy/aga‐update‐on‐revenue‐decoupling‐mechanisms.pdf
Arimura,ToshiH.,ShanjunLi,RichardG.Newell,andKarenPalmer(2011).“Cost‐
EffectivenessofElectricityEnergyEfficiencyPrograms.”ResourcesfortheFutureDiscussionPaperRFFDP09‐48‐REVrevisedApril2011.Availableat:http://www.rff.org/RFF/Documents/RFF‐DP‐09‐48‐REV.pdf
Asif,M.andT.Muneer(2007).“Energysupply,itsdemandandsecurityissuesfor
developedandemergingeconomies.”RenewableandSustainableEnergyReviews11(7):1388‐1413
Auffhammer,Maximilian,CarlBlumstein,andMeredithFowlie(2008).“Demand
SideManagementandEnergyEfficiencyRevisited.”EnergyJournal29(3):91–104
Baumann,David(2008).“TheEffectsofGovernmentalEnergyEfficiencyActivities
onElectricityConsumption–AnEconometricAnalysis.”LBJSchoolofPublicAffairs
Bhole,BhuratandSunitaSurana(2011).“ElectricityPricesandStateCommitment
toEnergyEfficiencyintheU.S.”EnergyEfficiency4:9‐16Blomquist,Glenn(1974).“TheEffectofElectricUtilityPowerPlantLocationonArea
PropertyValue.”LandEconomics50(1):97‐100Boonin,DavidM.(2009).“ARateDesigntoIncreaseEfficiencyandReduceRevenue
Requirements”ElectricityJournal22(4):68‐78Brennan,Tim(2009).“TheChallengesofClimateforEnergyMarkets.”RFF
DiscussionPaperNo.09‐32.
51
Brennan,Tim(2008)."’NightoftheLivingDead’or‘BacktotheFuture’?ElectricUtilityDecoupling,RevivingRate‐of‐ReturnRegulation,andEnergyEfficiency.”RFFDiscussionPaperNo.08‐27.
Brennan,Tim(2009)."OptimalEnergyEfficiencyPoliciesandRegulatoryDemand‐
SideManagementTests:HowWellDoTheyMatch?"RFFDiscussionPaperNo.08‐46
Brookings(2011).“EnergySecurityInitiative.”AccessedNov2011.Availableat:
http://www.brookings.edu/projects/energy‐security.aspxBryce,Robert(2010).“ABadBetOnCarbon.”TheNewYorkTimes.Availableat:
http://www.nytimes.com/2010/05/13/opinion/13bryce.htmlBureauofEconomicAnalysis(2011).“RegionalData:GDP&PersonalIncome.”U.S.
DepartmentofCommerceaccessedNov2011.Availableat:http://www.bea.gov/iTable/iTable.cfm?reqid=70&step=1&isuri=1&acrdn=1
Costello,Ken(2011).“SomeAdvicetoRegulatorsonFormulaRatePlans.”
ElectricityJournal24(2):44‐54CSI(CenterforStateInnovation)(2008).“UtilityRateDecoupling:Conserving
Energy:APolicyBriefbytheCenterforStateInnovation”CenterforStateInnovation.Availableat:http://www.stateinnovation.org/Publications/All‐Publications/Utility‐Rate/UtilityRates.aspx
Costa,DoraL,andMathewE.Kahn(2010).“WhyHasCalifornia’sResidentialElectricityConsumptionBeenSoFlatSincethe1980’s?AMicroeconometricApproach.”NationalBureauofEconomicResearchWorkingPaper15978.
Edelstein,PaulandLutzKilian(2009).“Howsensitiveareconsumerexpendituresto
retailenergyprices?”JournalofMonetaryEconomics56(6):766‐779ECW(EnergyCenterofWisconsin)(1997).“Market‐BasedUtilityDSMPrograms.”
Report,Aug1997.Availableat: www.ecw.org/ecwresults/162‐1.pdf
EIA(U.S.EnergyInformationAdministration)(1997).“ElectricityPricingina
CompetitiveEnvironment:MarginalCostPricingofGenerationServicesandFinancialStatusofElectricUtilities.”EnergyInformationAdministration–OfficeofIntegratedAnalysisandForecasting.Availableat:ftp://ftp.eia.doe.gov/electricity/0614.pdf
52
EIA(U.S.EnergyInformationAdministration)(2011).“FormEIA‐826DataMonthlyElectricUtilitySalesandRevenueData.”DepartmentofEnergy/EnergyInformationAdministration.Availableat:http://www.eia.gov/cneaf/electricity/page/eia826.html
EIA(U.S.EnergyInformationAdministration)(2011).“FormEIA‐861FinalDataFile
for2010.”DepartmentofEnergy/EnergyInformationAdministration.Availableat:http://www.eia.gov/cneaf/electricity/page/eia861.html
EnerStar(2012).“PowerCostAdjustment–FrequentlyAskedQuestions.”Accessed
Apr2012.Availableat:http://www.enerstar.com/ms_power_cost_adj.html
EnergyStar(2012).“LightBulbsforConsumers.”AccessedFeb2012.Availableat:
http://www.energystar.gov/index.cfm?fuseaction=find_a_product.showProductGroup&pgw_code=LB
EPA(EnvironmentalProtectionAgency)(2007).“AligningUtilityIncentiveswith
InvestmentinEnergyEfficiency:AResourceoftheNationalActionPlanforEnergyEfficiency.”EnvironmentalProtectionAgency.Availableat:http://www.epa.gov/cleanenergy/documents/suca/incentives.pdf
Espey,JamesA.,Espey,Molly,(2004)“TurningontheLights:AMeta‐analysisof
ResidentialElectricityDemandElasticities,”JournalofAgriculturalandAppliedEconomics,36(1):pp.65‐81
Eto,Joseph,StevenStoft,andTimothyBelden(1994).“TheTheoryandPracticeof
Decoupling.”LawrenceBerkeleyLaboratory.Availableat:http://escholarship.org/uc/item/9gp741dm;jsessionid=5E68872CEE40922AE7945995A9724D59#page‐1
GIllingham,Kenneth,RichardNewell,andKarenPalmer(2009).“EnergyEfficiency
EconomicsandPolicy.”ResourcesfortheFutureDiscussionPaper09‐13April2009
GIllingham,Kenneth,RichardNewell,andKarenPalmer(2006).“EnergyEfficiency
Policies:ARetrospectiveExamination.”AnnualReviewEnvironmentalResources31:161‐92
Glaeser,EdwardL,andMathewE.Kahn(2008).“TheGreennessofCities:Carbon
DioxideEmissionsandUrbanDevelopment.”WorkingPaper14238NationalBureauofEconomicResearchAug2008
53
Graniere,RobertJ,Cooley,Anthony(1994).“DecouplingandPublicUtilityRegulation.”TheNationalRegulatoryResearchInstituteReportNRRI94‐14Aug1994.Availableat:http://nrri.org/pubs/electricity/94‐14.pdf
Hausman,Jerry(1979).“IndividualDiscountRatesandthePurchaseand
UtilizationofEnergy‐UsingDurables.”BellJournalofEconomics,10(1):33–54
Hansen,D.G.(2007).“AReviewofNaturalGasDecouplingMechanismsand
AlternativeMethodsforAddressingUtilityDisincentivestoPromoteConservation.UtahDepartmentofPublicUtilities,DocketNo.05‐057‐T01,DPUExhNo.6.1(DGH‐A.1)
Holland,S.P.,Mansur,E.T.(2008).“IsReal‐TimePricingGreen?:TheEnvironmental
ImpactsofElectricityDemandVariance.”ReviewofEconomicsandStatistics90(3):550‐561
Hurley,Doug,KenjiTakahashi,BruceBlewald,JenniferKallay,andRobinMaslowski
(2008).“CostsandBenefitsofElectricUtilityEnergyEfficiencyinMassachusetts.”SynapseEnergyEconomics,IncFinalReport.August2008.Availableat:http://www.synapse‐energy.com/Downloads/SynapseReport.2008‐08.0.MA‐Electric‐Utility‐Energy‐Efficiency.08‐075.pdf
IPCC(IntergovernmentalPanelonClimateChange)(2007).“ClimateChange2007:
SynthesisReport.”IPCCFourthAssessmentReport:ClimateChange2007.Availableat:http://www.ipcc.ch/publications_and_data/ar4/syr/en/mains2‐1.html
IMF(InternationalMonetaryFund)(2012).WorldEconomicOutlookdata.Accessed
2012.Ito,Koichiro(2010).“Doconsumersrespondtomarginaloraverageprice?Evidence
fromnonlinearelectricitypricing.”UniversityofCalifornia,BerkeleyDraftPaper.Availableat:http://ecnr.berkeley.edu/vfs/PPs/ItoKoi/web/JMP_Koichiro_Ito_UC_Berkeley_2010_1122.pdf
Jaffe,AdamB.,andRobertN.Stavins(1995).“DynamicIncentivesofEnvironmental
Regulations:TheEffectsofAlternativePolicyInstrumentsonTechnologyDiffusion.”JournalofEnvironmentalEconomicsandManagement29(3):43–63
54
Joskow,Paul,andDonaldMarron(1992).“WhatDoesaNegawattReallyCost?EvidencefromUtilityConservationPrograms.”EnergyJournal13(4):41–74
Kahn,MathewE.andErinT.Mansur(2011).“DoLocalEnergyPricesandRegulation
AffecttheGeographicConcentrationofEmployment?ABorderPairsApproach.”NationalBureauofEconomicResearchWorkingPaper16538Jun2011.Availableat:ei.haas.berkeley.edu/pdf/working_papers/WP209.pdf
Kihm,Steven(2009).“WhenRevenueDecouplingWillWork…AndWhenItWon’t.”
ElectricityJournal22(8):19‐28Kotchen,MathewJandMichaelR.Moore(2007).“Privateprovisionof
environmentalpublicgoods:Householdparticipationingreen‐electricityprograms.”JournalofEnvironmentalEconomicsandManagement53:1‐16
Lazer,Jim,FrederickWeston,andWayneShirley(2011).“RevenueRegulationand
Decoupling:AGuidetoTheoryandApplication.”TheRegulatoryAssistanceProject(RAP)Jun2011.Availableat:www.raponline.org/document/download/id/902
LeagueofConservationofVoters(2010).“NationalEnvironmentalScorecard09:
SecondSession111thCongress,”LeagueofConservationofVoters.Availableat:http://www.lcv.org/scorecard/past‐scorecards/pdf/scorecare‐2010.pdf
LeagueofConservationofVoters(2011).“PastScorecards.”LeagueofConservation
ofVoters.Availableat:http://www.lcv.org/scorecard/past‐scorecards/
Lesh,PamelaG.(2009).“RateImpactsandKeyDesignElementsofGasandElectric
UtilityDecoupling:AComprehensiveReview.”ElectricityJournal22(8):65‐71
Linn,Joshua(2008).“EnergyPricesandtheAdoptionofEnergy‐SavingTechnology.”
TheEconomicJournal118(533):1986‐2012Loughran,DavidS.,andJonathanKulick(2004).“Demand‐SideManagementand
EnergyEfficiencyintheUnitedStates”.EnergyJournal25(1):19–41MagaliDelmas,MichaelV.Russo,MariaJ.Montes‐Sancho(2005)."Deregulationand
ResourceReconfigurationInTheElectricUtilityIndustry"UniversityofCaliforniaEnergyInstituteApril2005.Availableat:http://www.ucei.berkeley.edu/PDF/EPE_012.pdf
55
McCarthy,KevinE.(2009).“ElectricRateDecouplinginOtherStates.”OLRResearchReportJan2009.Availableat:http://www.cga.ct.gov/2009/rpt/2009‐R‐0026.htm
McKinsey&Company(2007).“ReducingU.S.GreenhouseGasEmissions:HowMuch
atWhatCost?”US.GreenhouseGasAbatementMappingInitiativeExecutiveReport
MenekenH.L.(2007).“RevenueDecoupling:APolicyBriefoftheElectricity
ConsumersResourceCouncil.”TheElectricityConsumersResourceCouncilJan2007
Michelfelder,Richard(1993).“EvolvingElectricUtilityRegulatoryPolicy:
InternalizingtheSocialCostsofProduction.”TheAmericanJournalofEconomicsandSociology52(2)227‐239.Availableat:http://www.jstor.org/stable/3487062
Moore,ThomasG.(1970).“TheEffectivenessofRegulationofElectricUtilityPrices.”
SouthernEconomicJournal36(4):365‐375Musti,Sashank,KatherineKortum,andKaraM.Kockelman(2011).“Household
energyuseandtravel:Opportunitiesforbehavioralchange.”TransportationResearchPartD1649‐56.]
NARUC(NationalAssociationofRegulatoryUtilityCommissioners)(2007).
“DecouplingofElectric&GasUtilities:FrequentlyAskedQuestions(FAQ).”NationalAssociationofRegulatoryUtilityCommissioners2007.Availableat:http://www.naruc.org/Publications/NARUCDecouplingFAQ9_07.pdf
NationalWeatherServiceClimatePredictionCenter(2012).“DegreeDaysStatistics.”
AccessedFeb2012.Availableat:http://www.cpc.ncep.noaa.gov/products/analysis_monitoring/cdus/degree_days/
Parformak,PaulW.,andLesterB.Lave(1996).“HowManyKilowattsAreina
Negawatt?Verifying‘ExPost’EstimatesofUtilityConservationImpactsattheRegionalLevel.”EnergyJournal17(4):59–88
PSC(DelawarePublicServiceCommission)(2007).“BeforethePublicService
CommissionoftheStateofDelaware,intheMatteroftheInvestigationofthePublicServiceCommissionintoRevenueDecouplingMechanismsforPotentialAdoptionandImplementationbyElectricandNaturalGasUtilitiesSubjecttotheJurisdictionofthePublicServiceCommission”.PSCRegulationDocketNo.59Mar2007
56
PSC(PublicServiceCommissionofWisconsin)(2001).“TypicalStepsinaMajorRateCase.”PublicServiceCommissionofWisconsin.Availableat:psc.wi.gov/thelibrary/publications/general/general04.pdf
PUCO(PublicUtilitiesCommissionofOhio)(2011).“RateCaseProcess.”Public
UtilitiesCommissionofOhioaccessedOct2011.Availableat:http://www.puco.ohio.gov/puco/index.cfm/consumer‐information/consumer‐topics/rate‐case‐process/
Saad,Lydia(2011).“InU.S.,ExpandingEnergyOutputStillTrumpsGreenConcerns.”
Gallup.Mar2011.Availableat:http://www.gallup.com/poll/146651/Expanding‐Energy‐Output‐Trumps‐Green‐Concerns.aspx
Smil, Vaclav (2011), Energy Transitions: History, Requirements, Prospects. Praeger. Stern,N.(2008).“TheEconomicsofClimateChange.”AmericanEconomicReview
98(2):1‐37Train,KennethE.andJudiE.Strebel(1987).“EnergyConservationandRebatesin
CommercialFoodEnterprises.”AmericanAgriculturalEconomicsAssociation69(1):106‐114
57
AppendixA–ModelResultsTable1:
Regressions of Log Residential Energy Consumption Per Customer (1) (2) (3) (4)
OLS 2SLS 2SLS -
Robustness Pre-existing
Trend Decoupling -0.05** -0.01 -0.01 x10 (-2.509) (-0.550) (-0.600) DSM x 0.3411** 0.3711** 0.1012 (2.283) (2.390) (0.964) Decoupling*DSM x -0.3911** -0.4111** x (-1.981) (-2.005) Res. Customers -1.00*** -1.00*** -1.00*** -1.00*** (-405.390) (-407.717) (-407.849) (-743.815) Electricity Price x -1.47*** -1.42*** -0.11 (-3.185) (-3.039) (-0.090)
Natural Gas Price -0.1211 0.0811 0.0611 0.1311
(-0.712) (0.444) (0.355) (0.992) GDP 0.25** 0.26*** 0.24*** -0.13 (2.576) (2.785) (2.788) (-0.679) Pop 0.09 0.07 0.07 0.34* (0.941) (0.716) (0.744) (1.913) Personal Income -0.2711 -0.2211 -0.2211 -0.9411*** (-1.610) (-1.296) (-1.219) (-6.909) EERS 0.01 0.02 x 0.01 (0.794) (1.320) (0.786) Env. Sensitivity 0.0311 0.02 x -0.02 (1.208) (0.928) (-1.209) CDD 0.1111*** 0.1111*** 0.1111*** 0.1211*** (13.443) (13.338) (13.368) (27.607) HDD 0.0211*** 0.0211*** 0.0211*** 0.0411*** (5.463) (5.248) (5.243) (28.215) Year x x x 0.02** (2.394) Year*Decoupling x x x 0.01** (2.082) √ √ √ √
Controlled for Utility
√ √ √ x
Controlled for Time
2.70**
Constant (2.465)
N 44,718 44,656 44,656 21,263 R2 0.986 0.977 0.977 0.983 t-statistics clustered on utility in parentheses *** p<0.01, ** p<0.05, * p<0.1
10Omittedbecauseofcollinearity11Coefficientmultipliedby100
58
Table2:Regressions of Log Total Annual Utility DSM
Expenditures (1) (2) (3) OLS Tobit Quantile Decoupling 0.04 0.05 0.34* (0.074) (0.090) (1.855) Res. Customers -0.01 -0.00 -0.00 (-0.147) (-0.084) (-0.169) GDP 1.86 2.51 -0.11 (0.581) (0.668) (-0.204) Pop 1.04 1.39 1.78* (0.250) (0.303) (1.836) Personal Income -0.09 -0.15 0.00 (-0.578) (-0.788) (0.000) EERS 1.96 2.02 0.72*** (1.415) (1.423) (2.804) Env. Sensitivity 0.01 0.01 0.00 (1.004) (1.194) (0.315) CDD 0.00 0.00 -0.00 (0.379) (0.415) (-0.000) HDD -0.00 -0.00 -0.00 (-0.157) (-0.139) (-0.000) Controlled for Utility √ √
√
Controlled for Time √ √
√
Constant -13.98 -21.38 9.01 (-0.413) (-0.533) (1.569) N 1,502 1,502 1,501 (Pseudo) R2 0.901 0.291 0.727 t-statistics in parentheses (clustered on utility for OLS and Tobit) *** p<0.01, ** p<0.05, * p<0.1
59
Table3:First-Stage Regressions of Residential Electricity Price (1) (2) (3) Decoupling 0.00 0.01* 0.00 (0.772) (1.849) (0.718) DSM -0.00 x 0.00 (-0.167) (0.050) Decoupling*DSM 0.1012* x 0.1012 (1.699) (1.648) Res. Customers -0.00 -0.00 -0.00 (-0.516) (-0.463) (-0.559) Natural Gas Price 0.0412*** 0.0412*** 0.0412*** (3.761) (3.608) (3.531) GDP 0.00 0.00 -0.00 (0.082) (0.176) (-0.129) Pop -0.02 -0.02 -0.02 (-0.991) (-1.081) (-1.009) Personal Income 0.0312* 0.0312* 0.0312* (1.881) (1.850) (1.949) EERS 0.00 0.00 x (1.141) (1.128) Env. Sensitivity 0.0112 0.0112 x (1.537) (1.512) CDD 0.00 0.00 0.00 (0.287) (0.295) (3.531) HDD -0.0112*** -0.0112*** -0.0112*** (-5.585) (-5.581) (-5.622) 0.0213** 0.0213** 0.0213**
% Gen Coal*Price Coal (2.459) (2.485) (-3.585)
0.0413*** 0.0413*** 0.0413***
% Gen Gas*Price Gas (9.317) (9.316) (2.394)
-0.0213*** -0.0213*** -0.0213*** % Gen Oil*Price Oil (-4.942) (-4.979) (9.319) -0.0313*** -0.0313*** -0.0313***
% Gen Renew*Price Coal (-3.551) (-3.689) (-4.926)
√ √ √
Controlled for Utility
√ √ √
Controlled for Time
0.13 0.12 0.16
Constant (0.996) (0.925) (1.211)
N 44,656 44,656 44,656 R2 0.900 0.900 0.900 t-statistics clustered on utility in parentheses *** p<0.01, ** p<0.05, * p<0.1
12Coefficientmultipliedby10013Coefficientmultipliedby10,000
60
Table4:
Probit Regressions of Probability of Decoupling (1) (2) (3) Res. Sales per Customer - 2001 0.28*** 0.23***
0.23*** (3.097) (3.333) (2.929)
Res. Customers - 2001 0.18*** 0.20*** 0.19*** (2.672) (2.627) (2.668) GDP per capita - 2001 2.28** 2.80*** 2.29** (2.569) (2.690) (2.575) Personal Income - 2001 -0.15 -0.11 -0.14 (-1.138) (-0.712) (-1.094) EERS - 2001 -0.38 0.59 -0.38 (-1.148) (1.203) (-1.130) Env. Sensitivity - 2001 0.01** 0.01** 0.01** (2.141) (2.087) (2.153) CDD - 2001 0.1414 0.1214 0.1314 (1.265) (0.929) (1.269) HDD - 2001 -0.0114 -0.0114 -0.0114 (-0.330) (-0.136) (-0.319) Electricity Price - 2001 5.07 3.20 5.01 (1.220) (0.653) (1.199) % Gen from Coal - 2001 -0.01 -0.01 -0.01 (-1.581) (-1.254) (-1.591) % Gen from Gas - 2001 -0.01 -0.02* -0.01 (-1.314) (-1.724) (-1.310) % Gen from Renewables - 2001 -0.01 -0.01
-0.01 (-0.822) (-0.718) (-0.839)
Δ15 Res. Sales per Customer 0.56 0.02
x (0.995) (0.288)
Δ Res. Customers x 0.56 x (0.978) Δ GDP per capita x 5.21 x (1.522) Δ EERS x 1.67** x (2.313) Δ Env. Sensitivity x 0.01 x (.721) Δ Electricity Price x 9.01 x (1.247)
Constant -26.24*** -32.68*** -26.42***
(-2.783) (-2.898) (-2.793) N 384 384 384 Pseudo R2 0.347 0.421 0.348 z-statistics in parentheses *** p<0.01, ** p<0.05, * p<0.1
14Coefficientmultipliedby10015Δ=value2005–value2001
61
AppendixB–VariableDescriptionsResidentialelectricityconsumptionpercustomer~Inaccordancewiththe
techniquesofArimuraetal.(2011)andLoughranandKulick(2004),variableson
monthlyresidentialenergyconsumptionpercustomerforeachutilityandyear
werecalculatedfrommonthlyenergyconsumptiondatafromFormEIA‐826and
annualenergycustomerbysectordatafromFormEIA‐861.Foreachutility,year,
andsector,monthlyconsumptiondataweredividedbythecorrespondingnumber
ofcustomersforthatyeartoattainestimatedelectricityconsumptionpercustomer.
Consumptionismeasuredinmegawatthours(MWh).Thisanalysisusesthenatural
logarithmoftheresidentialelectricityconsumptionpercustomer.Thisstudyuses
nominalconsumption,althoughtheuseofrealconsumptionwouldnotalterthe
resultsduetolinearityofthelogarithmicfunction16.
DSM~DataonannualtotalutilityspendingonDSMprograms(measuredin
dollars)wereextractedfromFormEIA‐861.Thisvariableshouldreflectallofa
utility’snominalspending–directandindirect–inagivenyearonDSMprograms.
Tokeeputilitieswith$0DSMexpenditureinthedata,thevariableusedinthe
analysisisthenaturallogarithmof1+nominalDSMspending.
Intheory,theDSMvariableshouldcaptureonlyspendingonresidentialDSM
andshouldbemeasuredperresidentialcustomer.Unfortunately,DSMspending
wasnotbrokendownbysectorformostoftheyearsinthisstudy.Dataonthe
breakdownofDSMexpendituresbyutilityin2010,however,areavailable.In2010,
lessthanhalfofDSMexpenditureswereusedforprogramsintheresidentialsector.
ThisintroducesconsiderablemeasurementerrorinthemeasureofDSM.
DSMspendingdataismissingforsomeutilitiesinsomeyearsinEIAForm
EIA‐861.Thisispresumablybecausemanyutilitieschosetowithholdinformation
ontheirDSMspendingfromtheEIAduringyearswhentheirspendingislowor16log(realconsumption)=log(nominalconsumption/priceindex)=log(nominalconsumption)–log(priceindex)=log(nominalconsumption)–c1.Iflog(realconsumption)=BX+c2,thenlog(realconsumption)=BX+(c1+c2)=BX+c3wherec’sdenoteconstants.Thus,onlytheconstanttermisaffectedbythischoice.
62
nonexistent.Inthispaper,weassumethatutilitieswhodonotsubmitinformation
ontheirDSMspendinghadnoDSMspending.
Preliminaryanalysisexperimentedwiththenaturallogarithmsof1+total
DSMexpenditureand1+DSMexpenditurepercustomer.Bothhaveobviousflaws.
WhichisbetterdependsonthenatureofchangesinutilityDSMspendingovertime.
TheresultswhenDSMisthedependentvariablearesimilarregardlessofchoiceof
measure.WhenDSMisusedasanexplanatoryvariable,preliminaryanalysis
suggestedthattheformermeasurehadgreaterexplanatorypowerandistherefore
thefocusofthisanalysis.
Decoupling~Adummydecouplingvariablewascreatedusinginformationfrom
ACEEEandfromvariousonlinedockets.Thisvariabletakesthevalue1ifthe
specifiedutilityhadanytypeofdecouplingmechanisminplaceinthegivenmonth
andyear,andittakesthevalue0otherwise.
ResidentialCustomers~Annualdataonnumberofresidentialcustomersper
utilitywereretrievedfromFormEIA‐861.Thenaturallogarithmofnumberof
customerswasusedinthisanalysis.
ElectricityPrice~Monthlyutilityelectricityresidentialretailpriceswere
retrievedfromFormEIA‐826.Pricesareinunitsof$/kWh.
RetailNaturalGasPrice~Followingtheliterature,naturalgaspriceisincludedin
themodelsbecauseitisapotentialsubstituteforelectricity.Monthlyresidential
naturalgaspricesbystatewereacquiredfromtheEIANaturalGasPrices
ResidentialPriceDataSeries.Naturalgaspricesareindollarspercubicfeet.
GDP~InkeepingwithArimuraetal.(2011)andLoughranandKulick(2004),data
onannualnominalGDPpercapitabystatewereretrievedfromtheBureauof
EconomicAnalysisfortheyears2001‐2010.GDPismeasuredinthousandsof
63
currentdollars.ThenaturallogarithmofGDPwasusedintheanalysis.Eachannual
valuewasusedforallmonthlyobservationsinagivenstateandyear.
QuarterlyPersonalIncome~Dataonstatequarterlypersonalincomeinmillions
ofnominaldollarswereobtainedfromtheBureauofEconomicAnalysis.The
naturallogarithmofpersonalincomewasusedinthisanalysis.
Pop~AvariableforannualpopulationwascomputedusingannualstateGDPand
annualper‐capitastateGDPfromtheBureauofEconomicAnalysis.Thenatural
logarithmpopulationwasusedintheanalysis.Eachannualvaluewasusedforall
monthlyobservationsofconsumptioninagivenstateandyear.
EERS~AdummyvariableforwhetherornotthestatehadanEnergyEfficiency
ResourceStandardinplaceduringthegivenmonthandyearwasgeneratedbased
ondatafromACEEEandvariousdockets.
EnvironmentalSensitivity~Usingsimilarmethodstothoseofpreviousstudieson
electricityconsumption(Delmasetal.2005,Arimuraetal.2011),anannual
environmentalsensitivityratingwascalculatedforeachstatebasedonscoresfrom
theLeagueofConservationVoter’sNationalEnvironmentalScorecards.Thisrating
averagestheLeagueofConservationVoter‘smeanscoresofthepoliticiansinthe
houseandinthesenateofeachstate.Theratingsareonascaleof0to100andare
basedonhowthepoliticiansvoteonkeyenvironmentallegislation.
CDDandHDD~Population‐weightedmonthlyheatingandcoolingdegreedaysby
statewerecompiledfromtheNationalWeatherServiceClimatePredictionCenter
archiveddegreedaysstatistics.Experimentswithvariousclimateindicatorsand
functionalformsofCDDandHDDsuggestthattherespectivelinearmodelsbest
capturetherelationbetweenclimateandpercapitaenergyconsumption.
64
%GenerationfromOil/Coal/Gas/Renewables~Thesevariablesrepresentthe
percentageofelectricityinthegivenstatethatwasgeneratedin2005usingeachof
oil,coal,naturalgas,andenergyfromvariousrenewableenergysources,
respectively.ThesedatawereretrievedfromtheEIAwebsite.
USOil/Gas/CoalPrices~Theseseriesreflecttheinputpricesfacedbyproducers
ofelectricity.TheserieswereprocuredfromtheEIAwebsite.USoilrefinerprices
andnaturalgascitygatepriceswereavailableonamonthlylevel.UScoalprices
wereonlyavailableontheannuallevel.
AustralianThermalCoalPrice~MonthlydataonAustralianthermalcoalprice,a
prominentcoalpriceindex,weretakenfromtheInternationalMonetaryFund.
PricesareinU.S.dollarspermetricton.
i.Time~Eachobservationofthevariable,time,representsthemonth(ex‐February
2001)whenthecorrespondingconsumptionoccurred.Thisvariablewas
partitionedinto119variables,oneforeachofthemonthsexceptforJanuary2001.
Together,thesevariablescaptureallnationwidetimeandseasonaldiscrepancies.
i.UtilityID~EachutilityintheU.S.hasauniqueidentificationnumber.Dataonthe
variable,UtilityID,wereretrievedfromFormsEIA‐826andEIA‐861.Itdistinguishes
eachutilityinthedatasetsfromotherutilities.Additional,unofficialID’swere
createdforutilitiesthatextendedtomultiplestatestoenabletheseentitiestobe
treatedasuniqueutilities.Onedummyvariablewascreatedforeachutility.For
eachobservation,thevalueofoneofthesevariablesisoneandthevaluesoftherest
arezero.
top related