Policy Research Working Paper 7912

Residential Electricity Subsidies in Pakistan

Targeting, Welfare Impacts, and Options for Reform

Thomas Walker Ezgi Canpolat

Farah Khalid KhanAdea Kryeziu

Social Protection and Labor Global Practice GroupDecember 2016

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Abstract

The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent.

Policy Research Working Paper 7912

This paper is a product of the Social Protection and Labor Global Practice Group. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at twalker@worldbank.org.

This paper examines the economic and social implications of the current system of residential electricity subsidies in Pakistan, and assesses the potential to improve the system’s outcomes through alternative targeting and program design. The analysis is multi-disciplinary in nature, drawing on national household survey data, electric company data on household electricity consumption, a welfare database, and a specially commissioned qualitative assessment of household and service provider attitudes and experiences. Affordability

is only one of many concerns among electricity users, with reliability of supply and customer service being arguably more important. The analysis finds that targeting could be improved considerably by allocating subsidies according to proxy-means test scores using an existing national proxy-means test database. Providing a flat credit rather than a price subsidy could also alleviate certain governance con-cerns. The paper concludes with some guidance on how to carry out these reforms based on international experience.

ResidentialElectricitySubsidiesinPakistan1Targeting,WelfareImpacts,andOptionsforReform

ThomasWalker*EzgiCanpolat*

FarahKhalidKhan*AdeaKryeziu*

Keywords:ElectricUtilities,Subsidies,Welfare,SafetyNets,Targeting,Pakistan.JELcodes:L94,H22,D6,I38.

*SocialProtectionandLaborGlobalPractice,TheWorldBankGroup.1TheauthorsthankPabloGottret,GulNajamJamy,AmjadZafarKhan,IftikharMalik,LucianPop,MohammadSaqibandRichardSpencerfortheirsupport.Theauthorsalsoappreciatetheassistanceandadviceofofficialsin the Government of Pakistan, specifically theMinistry ofWater and Power,Ministry of Finance, BenazirIncomeSupportProgramme,NADRA,andPlanningCommission.Inaddition,theauthorsareappreciativeofthegenerosityofofficialsatIESCO,FESCOandGEPCOforsharingconsumerbillingdataanalyzedinthisreport.QualitativeanalysisreferencedinthispaperwascarriedoutbySoSecInternational.TheworkwasfinancedbyagrantfromtheUnitedKingdomDepartmentforInternationalDevelopment,undertheTowardsIntegratedSocialProtectionSystemsinPakistantrustfund.

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I. Introduction

ThecostofresidentialelectricitysubsidiesinPakistanconstitutedaround0.8percentofGDPin2014–15,aboutthesameastotalexpenditureonthehealthsector.Attimesinthepastdecade, electricity subsidies have cost the government more than 2 percent of GDP,contributingtothenationaldebtandweakeningthecountry’sexternalposition.Aspartofitsenergysectorreforms,theGovernmentofPakistanhasinrecentyearsmadeeffortstoreform electricity subsidies, contributing to reducing their budgetary cost to around 0.4percentofGDPin2015‐16.Thisreductionhasbeenachievedpartlythroughcutstosubsidiesonthehighest‐volumeresidentialconsumers(aswellascommercialandindustrialusers),helpedbydecliningcostsofenergyworldwide.However,anyfuturehikesininternationalenergypriceswouldneedtobepassedontotheconsumer,withadverseconsequencesforpoverty,orabsorbedbythegovernmentasnewdebt.

Thereisagrowingbodyofinternationalevidencedemonstratingthatenergysubsidieshavebeensomeofthemostregressiveandcostlyfiscalpolicies,particularlyforthedevelopingworld(WorldBank,OECD&OPEC2010).In2015,globalsubsidiesreachedUS$5.3trillion,or6.5percentofglobalGDP(Coadyetal.2015a).Whilesubsidiesareoftenintroducedwiththe intention of reducing poverty, redistributing wealth in resource‐rich economies,protectingconsumersagainstlargepriceswings,orpromotingaccesstoenergy,theyareaninefficienttoolforachievingthesepurposes.Energysubsidiesputsignificantpressureonacountry’s fiscal balances, consumingpublic funds that could otherwise be used formoreeffectiveprograms.Thesesubsidiesalsotendtoberegressive,disproportionatelybenefitingthe better‐off. They discourage investments in renewable energy and promoteoverconsumption of energy and investment in energy‐intensive heavy industries.Recognizing this, many countries around the world are now rolling back or eliminatingenergysubsidies(Clementsetal.,2013a).

Despitecutstotariffsonheavyusers,electricitysubsidiesinPakistancontinuetobepoorlytargeted.ResidentialconsumersinPakistanarechargedelectricitytariffsbasedonmonthlyelectricityconsumption,withthemostgeneroussubsidiesprovidedtohouseholdswithlowandmoderateusage.Theeffectivenessof this targetingmechanismasasocialprotectionpolicy relies on thepremise thatmeasured electricityuse is closely related tohouseholdwelfare. But as we show in this paper, the correlation between measured electricityconsumptionandhouseholdwelfareinPakistanisrelativelyweak,meaningthatelectricitysubsidies continue to benefit the richest households disproportionately. Even after therecent reforms, the group receiving the greatest share of electricity subsidy expenditureremains the richest20percentof thepopulation.Theaverage subsidy for the richest20percent of households is 40 percent higher than the average subsidy for the poorest 20percentofhouseholds.Moreover,thereisastrongseasonalityofelectricityconsumption,withbothrichandpoorhouseholdsconsumingmoreinthesummermonths.Thispusheseven the poorest households into higher‐tariff slabs, increasing their bills substantially.Conversely,manyricherhouseholds‘drop’intothemoreheavilysubsidizedandlifelineslabsduringthewintermonths.

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Based on qualitative research commissioned for this paper, we find that in spite of thesubsidies, low‐ and lower‐middle incomehouseholds in Pakistan struggle to afford theirbasicelectricityneeds.Somehouseholdsreportedbeing forcedtoreduceexpenditureonfood, health and childcare in order to afford electricity bills. Such coping mechanismsparticularlyaffectwomen,whoarethemainconsumersofelectricityatthehouseholdlevel.Asidefromaffordability,residentialelectricityusersaremostconcernedaboutthereliabilityof supply and quality of customer service. Electricity is central to the lives of modernPakistanihouseholds,andtheirlivesaredisruptedbylonghoursofloadsheddingcommoninrecentyears.Thestressofcopingwiththehighcostandlowreliabilityofelectricity istaking a toll on family life, health, education, and economic activities. Low‐incomehouseholds—in particular urban slum residents and beneficiaries of the country’s mainwelfareprogram—mentionedresortingtoillegalelectricityconnectionsbecausetheycouldnotaffordtopaytheirbills.Inaddition,thequalitativeresearchrevealedagenerallackoftrustinelectricityserviceprovidersandapoorperceptionofgovernanceinthesector.

Householdsneedsupporttomanagerisingandvolatileenergycosts,butassistancecanbedesignedinawaythat is lessdistortionarytopricesand incentives,andmoreeffectivelytargetedto thepoor thantheexistingprice‐basedsubsidies.Pakistanhasstate‐of‐the‐arttargeting and registration mechanisms available to deliver better targeted assistance. Anational proxy means test (PMT) database developed for the Benazir Income SupportProgram could be used to target assistance to households based on their welfare. Analternativewouldbetouseexclusionfilterslikelandorvehicleownership,ortaxrecords.Targetingsubsidieswouldhelpensurethatassistancegoestothosehouseholdsthatmostneedit,whileexcludingtherichestconsumerswouldsaveconsiderableresources.Providingbillcreditsinplaceofprice‐basedsubsidieswouldmakebillingsimplerandprovideequalassistance to all targeted households. Other forms of assistance can help encourageconsumerstousetheformalelectricitysupply,cuttingdownonnon‐technicallossesinthesector.Thequalitative analysis, for instance, identifiedaneed formore flexiblepaymentoptions,andpointstoawaiveroflatepaymentfeesforthepoorerhouseholdsasawayofhelpingtokeepthemconnected.Measuressuchasconnectionfeewaiversandamnestyonkundauserscouldalsohelpattractmoreconsumersbackintotheformalsystem.

Experiencefromsubsidyreformepisodesworldwidestressestheimportanceofdevelopinganeffectivecommunicationplanfromthebeginning(Clementsetal.2013a).Thequalitativeresearchfindingsrevealedthatmanylower‐incomehouseholdsareunawarethatthereareelectricity subsidies, and do not understand the need for tariffs to increase. There is aperception that prices are already ‘too high’, and this encourages the use of illegalconnections. To ensure the reform is publicly accepted, it is crucial to develop acommunicationstrategytoincreasepublicawarenessaboutsubsidies,theplannedreform,andmeasurestomakeelectricitymoreaffordableforthosemostinneed.Consumersmightbemoreconvincedtopayhigherpricesforelectricityiftherearecredibleexpectationsofimprovementinthereliabilityoftheelectricitysupplyinthemediumterm.Thegovernmentshouldalsoaddress(andideallymitigate)knowngovernanceandaccountabilityissuesinthe sector in order to convince the public that the reform is worthwhile. For instance,grievanceredressmechanismsrelatedtoconnectionandbillpaymentcouldbestrengthenedandbetterpublicized.

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II. Country Background and International Experience with EnergySubsidyReforms

Pakistan’spower sector faces significant challenges in termsof capacity, governanceandfinancial sustainability. Residential and industrial electricity consumers have beenprofoundlyaffectedbyroutinepoweroutages,or ‘loadshedding’,wherebytheelectricitysupplyisperiodicallycutoffincertainareastorationsupplyduringpeakperiods.Inrecentyears load shedding has averaged 8 to 10 hours a day in some areas of the country,constrainingproductionandemployment(IMF,2013a).Inordertoaddressthesechallenges,the Government of Pakistan has embarked on substantial reforms of the power sector.Pakistan's National Power Policy, approved in June 2013, envisages that “Pakistan willdevelop the most efficient and consumer centric power generation, transmission anddistribution system thatmeets the needs of its population and boosts its economy in asustainableandaffordablemanner”(GovernmentofPakistan2013).Aspartof itsenergysectorreforms,inOctober2013theGovernmentofPakistanincreasedresidentialelectricitytariffstohigher‐volumeconsumersandeliminatedsubsidiesoncommercialandindustrialsupply.

TheGovernmentofPakistanprovidesseveralsubsidiestoresidentialelectricityconsumers,thelargestbeingtheTariffDifferentialSubsidy(TDS),whichfollowingthereformsin2012‐13(FY13)comprised96percentofelectricitysubsidies.TheTDSisthedifferencebetweentheelectricitytariff(pluscertainsurcharges)paidbyconsumersandthe‘allowablecosts’ofelectricityutilitiesdeterminedbytheregulator,NEPRA.TheTDSenablesthegovernmenttomaintain an identical tariff structure for households across the country and to providesubsidiestosomeconsumers.ResidentialelectricitysubsidiesinPakistanarebasedonthemonthlyelectricityusageofeachcustomer.Thetariffstructureisbasedon‘slabs’ofmonthlyhouseholdconsumption,withtheunitcostofelectricityincreasingfromoneslabtothenextasshowninTable1.2Ahighlyconcessional‘lifelinetariff’isprovidedtohouseholdsthatuselessthan50kilowatthours(kWh)permonth.3Thelifelinetariffisintendedtoprotectthepoorbyallowingthemtoaffordaminimumamountofelectricity.However,thebenefitofthelifelinetariffiscurtailedbyaminimummonthlychargeofRs75,meaningthesubsidizedrateiseffectivelyonlypaidbyconsumerswithconsumptionbetween38and50kWhinagivenmonth.

In October 2013, the government increased tariffs for slabs above 200 kWh permonth(thereby splitting the second slab in two) and changed the method of calculating bills.Whereasbeforehouseholdspaidfortheirfirst100unitsatthe1‐100kWh/monthslabrate,thenext200atthe101‐300kWh/monthtariff,andsoon,householdsnowpaytheunitratefortheslabimmediatelybelowtheirtotalmonthlyconsumptionforallelectricityuptothat

2Thedescriptionhererelatestothestandardtariff.Thereisalsoa ‘timeofuse’tariff forthe1.4percentofhouseholdswithelectronicmeters(asofJune30,2015),whichchargesflatpeakandoff‐peakratesforallunitsconsumed.3IntheFY16notifications,yettobecomeeffective,thelifelineistoberestrictedtohouseholdsbasedonsanctionedloadandaverageconsumption.

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slab’supperbound,andtheunitrateonthesubsequentslabfortheremainder.Forexample,ahouseholdconsuming350kWh/monthpaysthe200‐300kWhslabtariffrateforthefirst300kWhusedandthe301‐700kWhtarifffortheremaining50kWhused.GivenanaveragecostofsupplyofaroundRs12in2015‐16,thetoptwoslabsarenolongersubsidized,butduetothe201‐300slabsubsidysomehouseholdsconsumingover300kWh/monthstillgetasmallsubsidy.

Despite the recent tariff adjustments, electricity subsidies remain poorly targeted andprovidelimitedsupporttovulnerablehouseholds.InapreviousWorldBankstudy,itwasillustratedthatelectricityconsumptionisweaklyrelatedtooverallwelfareinPakistan,andthereforericherhouseholdsstillbenefitdisproportionately fromsubsidies (Walkeret.al.2014).Meanwhile,poorhouseholdsstruggletoaffordhigherelectricitycostsandresorttocopingmechanisms that negatively impact their overall well‐being. Around one‐third ofhouseholds,themajorityofwhicharepoororlivinginremoteareas,remainunconnectedtothe grid and instead use more expensive or less efficient energy sources. Since energysubsidiesarepoorlytargeted,itisnaturaltoaskwhethertheremightbemoreefficientandequitablemeansofmakingenergyaffordable.Indoingso,however,onemustconsiderthedirect and indirect impacts on household welfare, through higher prices for electricity,alternativeenergy,andindirectlyonothergoodsandservices.Internationalexperiencewithenergy subsidy reforms emphasizes the importance of compensation to protect poorerhouseholds against adverse impacts of subsidy reforms, and raise public acceptance ofreforms. The choice of compensation method depends on the country’s economic andpolitical circumstances.When undertaking such reforms, it is important to consider theavailability of existing social programs, administrative capacity, fiscal soundness of thebudgets,aswellasthepoliticalcontext(Yemtsovetal., forthcoming).Suchcompensatorymeasures should be tailored to the likely impact of the reform on a variety of differentgroups.

Cash transfers are often introduced or augmented as a means of replacing or at leasttemporarilymitigatingtheadverseeffectsofsubsidyreform.Untargetedcashtransfersare

Box 1: Indonesia’s subsidy reform experience 

Indonesia is one of the flagship examples of successful subsidy reform. In 2005, the increase in international oil prices gave way to ambitious subsidy reforms, which proceeded in two stages (Clements et. al., 2013). In March 2005, the government raised gasoline and diesel prices by 33 and 27 percent respectively.  Kerosene, being the least regressive of the subsidized goods, was initially left unchanged. In the second round of reform later that year, all fuel prices were increased, and kerosene prices almost doubled as a result.  Had there not been a proper compensation  plan,  it  is  estimated  that  these price hikes  (particularly  of  kerosene) would  have  caused  the poverty headcount index to rise by 5.6 percentage points (Yemtsov et al., forthcoming). To mitigate such drastic impacts  on  the  poor  and  near‐poor  households,  the  government  introduced  a  two‐pronged  compensation package,  reallocating a significant share of  the savings  from  the subsidy  reform  towards social protection. A temporary (two‐year) unconditional cash transfer introduced in conjunction with the reforms, Subsidi Langsung Tunai, was provided to the poorest 35 percent of the population (well above the 16 percent poverty  line),  in order  to protect  the near‐poor and minimize political unrest  (Beaton and Lontoh, 2010). What was  then  the world’s largest UCT program proved to be largely successful in reaching the poor; the poorest quintile received 21 percent of  the benefits, while  the  second,  third and  fourth quintiles  received a  total of 40 percent. The compensation package also  included education, health and rural  infrastructure programs for the poor  (which were introduced later). 

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sometimesusedinoil‐exportingcountries(forexampleintheIslamicRepublicofIran),withallhouseholdsatleastinprincipleabletoaccessthecompensation.Targetedcashtransfers,ontheotherhand,remainoneofthemostpreferredsafetynettoolsavailable forenergysubsidy reform. The experience of Indonesia (see Box 1) illustrates that targeted cashtransferscanreducethepopulation’sopposition tosubsidyreform,andhelpassist thosemostinneed.InPakistan,thelargestcashtransferprogramistheBenazirIncomeSupportProgramme (BISP), a targeted program which reaches over 5 million households. Themonthlypaymenttobeneficiarieshasbeenincreasedby50%since2013,likelyoffsettingthebulkoftheadverseimpactofthe2013subsidyreform(Walkeretal.,2014).

III. DistributionalIncidenceofElectricitySubsidies

Webeginbyexamining the incidenceofsubsidiesusinghouseholdsurveydata,updatingfindingsfromanearliersurveypresentedinWalkeretal.(2014).Figure1showshowthecurrent residential tariff structure concentrates subsidies on households with low tomoderate monthly electricity consumption. However, the incidence of these subsidiesdependsonthepatternsofconsumptionbywelfarelevel.

To examine this relationship, we use data from the 2013‐14 Pakistan Survey of LivingStandards (PSLM) toconstruct totalmonthlyhouseholdconsumptionpercapita foreachhousehold (ameasure ofwelfare). Figure 2 shows the breakdownofmonthly electricityconsumptionbyslabforeachdecileofhouseholdpercapitaexpenditure.Whilethereisacleardifference inconsumptionacrossdeciles, thegraphshows that thevastmajorityofhouseholds except in the top decile consume less than 300 kWh/month, and thereforecontinue tobenefit fromsubsidiesevenafter the2013reforms.However, since the totalsubsidyprovidedtohouseholdswithmoderateconsumption(betweenaround150and300kWh/month) is greater than that for households below 150 kWh/month, the bulk ofsubsidiesstillgoestobetter‐offhouseholds.Onepotentialshortcomingoftheaboveanalysisisthatthesurveyasksabouttotalelectricityconsumptionovertheprecedingmonth.Self‐reportsmaybeinaccurate,ormayincludeexpenditureonotherformsofelectricalpowersuchasbatteriesoruninterruptedpowersupplies.Inordertocorroboratethesefindings,wenowexamineactualbillingdata.

Dataonmonthlyelectricityconsumption,alongwithotherhouseholddetails,wereobtainedfor325,926householdsfromthreeelectricitydistributioncompanies(DISCOs):GujranwalaElectric Power Company (GEPCO), Faisalabad Electric Supply Company (FESCO) andIslamabad Electric Supply Company (IESCO). 4 These DISCOs together serve almost 38percent of Pakistan’s residential electricity consumers. 5 The three DISCOs also cover asignificant share of northern Pakistan and include amix of semi‐urban, rural and urbanareas.For thisanalysis IESCO,FESCOandGEPCOeachprovideda10‐15percentrandom

4OtherDISCOswereapproachedfor inclusion in theanalysis,butdatacouldnotbesourcedwith therightspecificationsintimeforthisstudy.5ForabreakdownofbillingdatapleaserefertotheAppendix.

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sampleofhouseholdmonthlyelectricitybillingrecordsfortheperiodJuly2013toJune2014(thesameperiodduringwhichthePSLMdatawerecollected).6

The DISCO databases have a record of basic household characteristics and monthlyelectricityconsumption,buttheydonothaveanyinformationonthehousehold’swelfarelevel.Toobtainagoodproxyforwelfarelevel,wemergedthebillingdatawiththeNationalSocio‐Economic Registry (NSER), a near‐census of households in Pakistan conducted in2011.TheNSERhasdatafor27millionhouseholdsinPakistanonoccupationofthehead,household size, assets and dwelling characteristics. The government collected and usedthesevariablestocreateaproxymeanstest(PMT)scoreforeachhouseholdfortargetingofBISP. 7 The National Database and Registration Authority (NADRA), which manages theNSER, generously agreed tomerge the two databases for us, using the citizen’s nationalidentitycardnumber(CNIC)asacommonidentifier.8

AswellaslookingfordirectmatchesbetweenCNICsinthetwodatabases,NADRAalsousedits ‘family folder’ system to look for family links between CNICs in each database asillustratedinFigure3.Around45percentofthe325,926recordsintheDISCOdatabaseweresuccessfullymatched to theNSER data. This seems low, but is actually quite impressiveconsideringtheNSERdatabasewasputtogetherin2011,andmanyhouseholdsthatdidnothaveaCNICin2011mayhavesinceobtainedoneandrecordedit intheDISCOdatabase.AnothermajorreasonwhyrecordsdidnotmatchwasthatmanyCNICsinthebillingdataweremissingor invalid.Asrobustnesscheck,wecompared thematchedandunmatchedsamplesandfoundthattheydidnotdiffersubstantially(seeAppendixTableA2).Wearetherefore relatively confident that the omission of these households does not skew theresultsoftheanalysis.EventhoughwehavedataoneachmonthoftheyearJuly2013toJune2014,meterreadersareoftenunabletoreadeachmetereverymonth,sobillingdataareoftenestimatedinthesemonthsandbalancedattheendoftheyearorwhenthemeterisnextread.Toavoidintroducingthismeasurementerrorintotheanalysis,inthissectionwereportaveragemonthlyconsumptionovertheyear.

Table2summarizesbasiccharacteristicsofthedatabyquintile.Againweseeanincreasingbutveryweakrelationshipbetweenwelfarelevelandelectricityusage.Weusequintilesofthe PMT as themeasure ofwelfare rather than per capita consumption.9It can be seenimmediatelythatelectricityconsumptionisrelativelysimilaracrossthepopulationandisweaklycorrelatedwithpoverty.

6Dataprovidedforeachhouseholdincludedtheidentitycardnumberofthebillholder,nameandaddress,father/guardianname,kWhconsumedpermonthfor2013‐14(FY14),connectedload(inkWh),phase,andnumberofairconditioners.7ThePMTscoreisdesignedtocorrelatecloselywithhouseholdpercapitaexpenditure,enablingonetorankallhouseholdsinthecountryroughlyfrompooresttorichest.Itisbasedon23variablesrelatedtohouseholdstructure,dwellingcharacteristics,education,occupationalstatusandassets.8TheCitizen’sNationalIDCardNumber(CNIC)isanationaluniqueidentificationnumberprovidedtoadultcitizens.FurtherdetailsonthematchingprocessareprovidedintheAppendix,partA.9ThecutoffPMTscoresforeachquintileareasfollows:PoorestQuintile=0to22,Lower‐MiddleQuintile=22to29.7,MiddleQuintile=29.7to37.4,Upper‐MiddleQuintile=37.4to46.4,RichestQuintile=46.4to95.17.

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Figure4replicatestheresultsofthePSLMdataanalysispresentedinFigure2.Therearesomekeydifferencesintheresults.Mostnotably,householdelectricityuseisconsiderablyloweraccordingtothebillingdata.Around30percentofthepooresttwodecilesconsumedlessthan50kWh/month(thelifelineslab)accordingtothebillingdata,comparedtolessthan10percentinthePSLMdata.Again,thismaybeduetoreportingofotherelectricityexpenses(suchasbatteries)inthehouseholdsurveymeasure.Despitethegenerallylowerconsumption levels, however, the pattern across the welfare distribution is similar:electricityconsumptionrisesgraduallywithwelfare,butalmostallhouseholdsstillconsumelessthan300kWh/monthandthereforebenefitfromsubsidies.Thisgraphalsoimpliesthatthesubsidycutsin2013likelyhadadirectimpactononlyasmallproportionofhouseholds,sincethetariffincreaseswererestrictedtoslabsabove200kWh/month.

Figure5showsthatthedistributionofsubsidiesisdisproportionatelyinfavoroftherichesthouseholds,withthetop20percentofhouseholdsreceivingabout24percentofthetotalsubsidy.Itcanalsobeseenthatthe50‐100and100‐200kWh/monthslabsaccountforthemajorityofsubsidies:anysubstantialcutstosubsidieswillneedtobefocusedontheseslabs,andthiswouldadverselyimpactthemajorityoflowerandmiddle‐incomehouseholds.

The current subsidy system does not take into account natural intra‐year variation inelectricityconsumption.GivenPakistan’swarmsummerclimateandcoolwinters,electricityexpendituresvarywidelybyseason(Figure6).Evenpoorhouseholdsthatqualifyforthelifelineinthewinter(Q3)moveintohigherslabsduringthesummer(Q1&Q4).Inthewinter,around13percentofrichhouseholdsqualifyforthelifelinesubsidy.Thesefindingsindicatethatastaticsubsidyschemethroughouttheyearisfailingtoprotectthepoor,andprovidesan unnecessary benefit to the richest households in thewintermonths,when electricityaffordabilityislessofaconcern.

RobustnessChecks

Lowmatchrate

OuranalysisispredicatedontheassumptionthatthePMTscoresmatchedtothebillingdatatell us about the patterns of electricity consumption and welfare at the national level.However,only45percentofDISCOrecordscouldbematchedwiththePMTscorethroughtheNSER.10Arelativelysmallshareofrecordscouldnotbematchedduetoerrors in theCNICsrecordsintheDISCOdatabase.ThemajorityoftheunmatchedhouseholdscouldnotbefoundintheNSERsurveydata,however,likelybecausethosefamiliesdidnothaveaCNICatthetimeofthesurveyin2010.Thesurveyiscurrentlyintheprocessofbeingupdated,however,meaningthatinfuturethematchrateislikelytobesignificantlyhigher.

10Theunmatched55%willhavesimilarsocioeconomicbreakdownormightbeskewedtowardsthebetteroffhouseholdsasrecordsoftheinitialNSERsurveyshowsthatmostrefusalscamefrombetteroffhouseholds.TheK‐densityplotshowsthevarianceinPMTacrossthematchedsample(seeAppendix,partE).

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Tocheckforbiasesinthematchedsample,wecomparedtheaverageconsumptionforboththematchedandunmatchedsampleusingasimplet‐test,andfoundnosignificantdifferencebetweenthetwosamples.11

Tenanthouseholds

ItiscommoninPakistanforthenameontheelectricitybilltobethatoftheownerofthehouse,evenifthepropertyisrentedbyanotherfamily.Ifthisisthecase,itislikelythatthebetter‐off landlord’s PMT score is matched against the poorer tenant’s actual electricityconsumption, perhaps contributing to the low recorded consumption among wealthyhouseholds.

Todeterminewhetherthisaffectstheresultsofthestudy,welookattheextentofrentershipinthestudyarea.ThePSLM2013‐14dataindicatethatinruralareas,93percentoffamiliesown their house, while in urban households, home ownership was around 72 percent.However,thiscannotexplainalargepartofthefindingssincetheserviceareasofthethreeDISCOsarepredominantlysemi‐urbanandrural.Adistrict‐wiserepresentationofthebillingdatasamplecanalsobefoundintheAppendix.

Representativenessofthebillingdata

ThePSLMdataexaminedinPartIarenationallyrepresentative.Thebillingdatasampleisfully random, but comes fromonly three non‐randomly selectedDISCOs.Howmight theanalysis differ if the other DISCOs were included? First, we note that the three DISCOscoveredinthisanalysiscomprise38%ofallhouseholds.Beingbetter‐offdistricts,wewouldexpecttoseehigherelectricityconsumptionamongthissampleoverall.Thiswouldimplythatnationwidetherewouldbeproportionatelylesshouseholdsabovethe300kWh/monthlevel,reinforcingtheaboveanalysis.Thereisnoreasontoexpecttheconsumptionpatternsacrossquintilestodiffersignificantlygiventhelargesample.

Multipleconnections

The finalpotential concern is thathouseholdsmayhavemultiple connections, spreadingtheir consumption across meters and thereby understating their total consumption.Approximately83percentofthematchedsamplehasasinglemeterconnection(thatis,thebillpayer’sCNICappearedonlyonceinthedatabase),6percenthave2or3meters,and11percenthavemorethan3meters(seeAppendix,partA).Fortheanalysisweremovedallhouseholdswithduplicateobservations,sinceitisnotclearwhetherthisreflectsaneffortonthepartofhouseholdstoevadehighertariffsorissimplyanerrorintheCNICrecords.However,evenifwealthierhouseholdsareusingmultiplemeters,theyqualify(illegally)forsubsidiesdespitehavinghigheroverallelectricityconsumption.Thusthiswouldnotaffectourfindingthatthebulkofsubsidiesgotonon‐poorhouseholds.

11Resultsareavailableuponrequest.

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IV. SocialandGenderImpactsofEnergySubsidiesandReform

To examine issues related to energy access and affordability for low‐ and lowermiddle‐incomehouseholds,andtoinformthedesignofsubsidyreformsinapoliticallyandwelfare‐sensitiveway,aqualitativestudywascommissionedandsupervisedbytheWorldBankandcarriedoutbyalocalresearchfirm.ThestudytookplaceinthreeprovincesofPakistaninMay and June 2015. The firm conducted focus group discussions (FGDs) with 400participants fromsixdistricts, stratifiedby incomegroup (low‐incomeand lowermiddleincome),gender,and location(urbanandrural).12Inaddition,FGDswereheldwithBISPbeneficiariesandkatchiabadi(slum)residents.Allparticipantshadanelectricityconnection(either legal or illegal). In all, 44 FGDs took place, each with 8‐10 participants. Thediscussions covered a range of topics related to energy usage, affordability and servicequality,andexploredattitudestowardsubsidyreformsandcompensation.FollowingeachFGD, an individual participant was randomly selected to participate in an ethnographicinterview(EI)todiscusstheissuesinmoredetail.Finally,thestudyincluded12interviewswith BISP officers and energy company representatives, in order to get a governmentperspectiveontheissuesraised.FurtherdetailsonthemethodologyandsurveyinstrumentareprovidedintheAppendix(partF).

EnergyUseandSpendingPatterns

Electricity is central to the livesofhouseholdsandhouseholdsuseavarietyof electricalappliances.Nearlyallhouseholdsmentionedusingelectricityforlighting.Whilethetypeofelectricalappliancesusedbyhouseholdsdependsonwelfarelevelandlocation,nearlyallparticipantsindicatedthattheyuseelectricfansintheirhomes.MostBISPbeneficiariesandkatchiabadiresidents(thepoorestgroupsinterviewed)reportedusingwashingmachines,fridges,irons,TVsandmobilephonechargers.Lowermiddle‐incomehouseholdsreportedusingavarietyofelectricalappliances,includingpersonalcomputers,evaporativecoolers,juicers,vacuumcleanersandsewingmachines.Morethanhalfoftheresearchparticipantsmentionedusingelectricpumpstofillhouseholdwatertanks.Althoughthesewaterpumpsconsumealimitedamountofelectricity,thehouseholdwatersupplyisinterruptedifloadsheddingoccurswhentanksareempty.Respondentsengaged in farmingalsomentionedusingelectricpumpsfortube‐wellirrigation.Whilefarmershaverelativelyhigherelectricityuseonaverageforthisreason,householdsresidinginruralareasuseslightlylesselectricityonaveragethantheirurbancounterpartsduetolowerratesofapplianceuse(Figure7).Thisisnotjustduetolowerlivingstandards:duringthesummermonths,ruralfamiliescansleepoutsideatnight,andtherebyavoidtheneedforelectriccooling.

12Theaveragemonthly incomeofparticipantsvariesbasedonprovinceand location.Overall, thereportedaveragemonthlyincomeoflow‐incomerespondentswasbetweenRs13,050andRs14,675,representingthefirstandsecondquintilesaccordingto2011‐2012PSLM.TheaveragemonthlyincomeoflowermiddleincomeparticipantsrangedbetweenRs19,700andRs22,000,correspondingtothe3rdand4thquintilesaccordingto2011‐2012PSLM/HIES.

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As observed in theprevious section, household electricity expenditure is seasonal:moreelectricity is used and the per‐unit cost is higher during the summer months (May toSeptember)duetotheuseofelectricfansandcoolers.DuetothehotsummerweatherinPakistan,peopletakeshowersmorefrequentlyandneedtowashandirontheirclothesmoreoftenatthesetimes.Thisresultsinhigheruseofwaterpumps,washingmachinesandirons.Participantsalsomentionedusingfridgesmoreoftenduringthesummer.Ramadan,whichhastakenplaceduringthesummerforthepastfewyears,alsoincreasestheconsumptionofelectricity.Households stated that theyuse energy‐intensive foodprocessors and juicersmore during Ramadan to prepare for sehri and iftar.13Another reason is thatwork andschoolhoursareshorterduringRamadan,meaningmenandchildrenareathomeformoreoftheday,increasingtheuseoffans,lights,andotherelectricappliances.

Consumption of energy is highest during theweekends and evenings.Most respondentsmentioned doing household chores in the evenings and on weekends. Male householdmembersoftencomehomeatmiddayonFridays toprepare forprayers.Consumption ishigherduringtheweekendsduetothepresenceofworkingadultsandschoolchildren.OnSundayswomenusewashingmachinesandironmorepreparingschooluniformsfortheirchildren.

Womenandmenhavedifferentelectricityusebehaviors.Womenarethemainconsumersof electricity at the household level, being traditionally responsible for performinghouseholdchoresandtherefore theprimaryusersofelectricappliancessuchaswashingmachines,irons,refrigeratorsandfoodprocessors.Thewomeninterviewedwerefrequentlyinvolvedinhouseholdbudgeting,andappearedtobemoreawarethanmalerespondentsofhowtouseenergyefficiently.

Despitestrugglingwithhigherenergyprices,mosthouseholdsmakeitaprioritytopaytheirelectricitybillsontimetoavoidsurcharges.Mostrespondentsmentionedthatpovertyandunexpected shocks are themain reasons for nonpayment of electricity bills. Householdsexpressedempathytowardsthosewhoareunabletopaytheirbills;however,themajorityof research participants disapproved of illegal electricity use and believed that it wascontributingtohigheroveralltariffsandpoorelectricityservice.

CopingwithIncreasingEnergyCosts

Highenergycostsdiminishthephysicalandpsychologicalwell‐beingofhouseholds.Figure8 summarizes themain copingmethods by socioeconomic group. Both low‐income andlowermiddle‐incomehouseholdsreportedreducingspendingonfoodtopaytheirelectricitybills. Katchi abadi residents, BISP beneficiaries and low‐income households mentionedreducingthenumberofmealsconsumed,eatingchutney,onions,chiliesandroti(flatbread)morefrequently,andcuttingoutmeatandotherproteins.Thesehouseholdsalsoexpressedthattheycouldnotcutfurthertheiralreadyminimizedspendingonbasicneedssuchasfood.

13SehriisanIslamictermreferringtothemealconsumedbyMuslimsbeforefastingduringRamadan.IftarisoneofthereligiousobservancesofRamadanandisoftendoneasacommunity,withpeoplegatheringtobreaktheirfasttogether.

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Lowermiddle‐incomehouseholds,ontheotherhand,reportedswitchingtolower‐qualityfoods.Low‐incomehouseholdsalsoreportedcuttingspendingonchildcareandeducation(e.g. sending children to public schools, and economizing on school uniforms andequipment).Thisgroupofrespondentsalsoreportedreducinghealthexpensesbyavoidingdoctorvisits.Someruralhouseholdsalsoreportedsellinglivestockinordertopaytheirbills.Theseresultsareconsistentwiththefindingsofahouseholdbudgetingstudyconductedbythe Sustainable Development Policy Institute (SDPI, 2014). Finally, social isolation is anindirectresultofhigherenergyprices:somehouseholdsreportedhavingtostayawayfromsocialgatheringssuchasweddingsduetoalackofmoneytopayforthenecessaryclothingandgifts.

Householdsactivelyreducetheirenergyusagetomanagetheirelectricitycosts.Bothlow‐income and lower middle income respondents mentioned that they switch off lights inunusedspaces,stayinginoneroomwithallfamilymemberstousefewerlightsandfans,sleeping incourtyards inruralareas,washclothesbyhand,anduseelectricalappliancessparingly.Womenaremoreaffectedbysuchmeasuresastheirworkloadincreasesduetodecreaseduseofelectricappliancessuchaswashingmachines.Householdsalsoappeartoinvestinenergysavingappliances:68percentoflowermiddle‐incomehouseholdsreportedpurchasing energy saver bulbs and more efficient appliances. Respondents engaged infarmingemphasizedthepotentialsavingsfromswitchingtoalternativeenergysourcessuchassolarpower.

Payingbills in installments isanothercopingmechanismmentionedbyFGDparticipants.

Somerespondentsreportedthattheywouldnotprefertopaytheirbillsininstallmentsasitcreates additional stress on household members. When they pay in installments, theyconstantlyworryaboutwhethertheywillbeabletopayontime.Respondentsalsosawthismethodasunattractive,reportingthatitsometimesrequiredbriberyofofficials.Borrowingmoneyisalsoemployedasacopingstrategybysomerespondents.Aroundathirdoflow‐incomerespondentsmentionedborrowingmoneyfromtheirrelativestopayhighbills.The

Box 2: Ethnographic Interview I 

General information about the household 

The respondent lives in the village of Timargarh in Lower Dir, KPK, with his extended family of ten. For the last 35 years he has worked as a driver. His house is partially constructed and has four rooms. His wife takes care of all the household chores. Both of his children are deaf, and he pays their medical expenses out of his  limited income. He has a separate kunda electricity connection in addition to a functioning legal connection. 

Expenditures on energy sources 

Electricity  is mainly used  in his home for  lighting, and for appliances  including fans, a fridge and an  iron. The respondent stated that his electricity bills are usually delivered in the last week of the month at the local mosque. The amount varies from Rs. 200 to Rs. 1,000 per month. 

Coping mechanisms 

The respondent supplements his driver’s income with wages from agricultural work. In order to reduce electricity expenditures, his family makes an effort to turn off all extra lights and to minimize use of the fridge during the winter months. 

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respondents see borrowing money as a last resort coping strategy since this putsconsiderablestressonhouseholdsandnegativelyaffectsfamilyrelations.

Despitethesensitivityofthetopic,asmallshareofhouseholdsconcededthattheyresortedtoillegalelectricity(thekundasystem)becausetheycouldnolongercopewithincreasingelectricitycosts.Usersofthekundasystempayasmallamounttothelinemeneverymonthtopreventthemfromcuttingtheirillegalconnection.Somerespondentsmentionedthattheystartedusingthekundasystemaftertheirelectricitywasdisconnectedduetononpaymentofbills.AccordingtoFaisalandEatzaz(2014),percapitaincomeandtheconsumerpriceofelectricityarekeydeterminantsofelectricitytheft.Asmallnumberoflowermiddle‐incomehouseholdsalsomentionedusingthekundasystemintermittently.Theserespondentshavelegal connections but use the kunda system for high electricity consuming appliances.Respondentsalsomentionedthat theysharemeterswith theirneighbors,as theycannotaffordtohaveaseparatemeter.Respondentswhosharemeterspayless.However,theylackcontroloverthetotalelectricityconsumptionandthebillamountand, therefore,are lessinclinedtosaveelectricity.Also,householdswhoshareameterarelesslikelytoqualifyforsubsidies.

ExperienceswithServiceQualityandEnergySectorOfficials

Loadshedding

Themost commonconcern citedby researchparticipantswasnot the costof electricity,however,but rather thereliabilityof theservice.Respondents fromallgroupsexpresseddissatisfactionwithofficialsandwith the longhoursofunscheduled loadshedding.Longhoursofloadsheddingandelectricityoutageshavehadadverseimpactsontheeconomic,physical and socialwell‐beingof citizens.14Respondents fromvariousoccupationgroupssuchasshopowners,factoryworkers,andtailorsmentionedthatduetoloadsheddingtheirincomelevelshavedropped.Mostoftherespondentscomplainedthatduetoloadsheddingtheyareunabletousewaterpumpstogetwater;duetolackofelectriclighttheirchildrencannotstudyintheevening;andalackoffansandcoolersmeanstheycannotgetregularsleep during the summer. The psychologicalwell‐being of participants is also negativelyaffectedbyloadshedding:somereportedthattheycannotrelaxintheirhomesandthattheyfeelangryduetotheunavailabilityofelectricity.

Asthemainconsumersofelectricityatthehouseholdlevel,womenaremoreaffectedbyloadsheddingandbythehousehold’seffortstomanageelectricityexpenses.Nearlyallwomenparticipantsstatedthatduetolongandunpredictablehoursofloadshedding,theycouldnotuse appliances such as washing machines, irons, vacuum cleaners, and electric cookingappliances. Instead, they perform household chores manually, which increases theirworkloadandreducestimethatcanbespentoneducationalorincome‐generatingactivities.Femalerespondentsalsomentionedthatincome‐generatingopportunitiessuchasstitching

14Inthesummerof2015,aheatwaveinthecountrykilledmorethan1,300people,and65,000peoplesufferedheatstroke.Longhoursofpoweroutageswereafactor(Imtiazandur‐Rehman,2015). 

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and embroidery and housekeepingwere negatively affected by the unreliable electricityservice. Female respondents are also adversely affected by the stress of sleep‐deprivedhusbandsandchildreninthesummermonths.

Intheabsenceofelectricity,respondentsswitchtoalternativesourcessuchaselectricallychargedlightsandcandles.Candleswerethemostcommonalternativelightingsource,usedby65percent ofBISPbeneficiaries and44percentofkatchiabadi residents.Overall, 72percentofrespondentsreportedusingelectricallychargedbatterylights.Thesecarrycoststoo:householdsspentRs.200toRs.250onaverageeachmonthoncandles,whileabatteryoperatedlightcostRs.250.Asmallnumberoflowermiddle‐incomehouseholdsmentionedusinganUninterruptedPowerSupply(UPS)duringloadsheddinghours.ThepriceofUPSdevicesrangesfromRs.10,000toRs.60,000.

Billingsystem

Thesecondmostimportantproblemreportedbyrespondentswasapervasivelackoftrustinthebillingsystem,with80percentofrespondentscomplainingthattheirelectricitybillamountsdonotreflecttheiractualuse(Figure9).AsamaleBISPbeneficiaryinNawabshah,Sindh,stated,“withsomuchloadshedding,whyisthebillsohigh?Theyarenotreadingthemeter properly.” Such perceptions are in part due to the widespread practice of billestimation:duetoshortstaffing,meterreadersdonotvisiteveryhousemonthlybutrather‘estimate’ usage andmake an ex‐post adjustment. Thismay be a source of confusion toconsumers.Ontheotherhand,somerespondentsclaimedthatmeterreadersinflatedtheirbillsdeliberately.Thefactthatmanyhouseholds’billsaredeliveredtocommunalplacessuchasmosquesalsocontributestotheparticipants’skepticismthatthedistributioncompanygenuinely reads theirmeters.Unreliable service contributes to theperceptionof inflatedbills.With lesshours of electricity service, consumers expect lowerbills.Whenbills rise(probablyduetoprice increases), there isaperceptionamongconsumersthattheutilitycompanyischeating.Electricitycompanyrepresentativesalsoemphasizedthedifficultiestheyfacewithmeterreadingduetostaffshortagesanddifficultyinaccessingsomelocalities.Meanwhile, thegovernment istakingsomemeasuressuchastakingphotosofmeters forbilling,tobuildtrustbetweenserviceprovidersandconsumers.

Governance

Amajority of participants complained about the attitude of electricity company officials,perceivingthemasrudeandunresponsive.Around81percentofrespondentsstatedthatcorruptionwas a significant problem in their interactionswith service providers. In thewordsofalow‐incomemaleintervieweeserviceprovidersare“forcingeveryonetocommitsinsbypayingbribes.”Meterreaders,theprimarypointofcontactbetweentheconsumersandelectricityproviders,wereperceivedascorruptby44percentofurbanrespondentsand29percentofruralrespondents,while32percentofurbanrespondentsand37percentofruralrespondentscomplainedabouttheirrudeattitude.Briberyofanofficialwasreportedby 65 percent of respondents, either to overcome issues related to overbilling, resolvetechnical problems, or in some cases to get an illegal electricity connection. The generalperceptionamong theparticipantswas thatwithoutbribesnoproblemwouldbesolved.

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Therewasalsogeneraldissatisfactionwiththeineffectiveanduntimelyresponseofserviceproviders to technical problems such as transformer breakdowns. All respondentswereawareoftheelectricitycompany’scomplaintoffices,andmanymalerespondentshadvisitedthematleastonce.However,asubstantialnumberofrespondentsreportedhavinggivenupontheircomplaintsaftervisitingtheoffice.WealsospoketobothDISCOofficials,andtheyexplained that conditions for good service and accurate billing were made difficult byresourceconstraints,especiallyshort‐staffing.

SocialAssistance

Energyaffordabilityassistanceisarguablypartofthesocialsafetynet.Ifsubsidiesarenothelping households to afford basic electricity needswithout resorting to harmful copingmechanisms, improved assistance should be developed in the context of the country’sbroader safety net policy. BISP, Pakistan’s largest safety net scheme, is an antipovertyinitiativecoveringover5millionhouseholdsandprovidingmonthlycashtransfersaswellas other support. Despite its size, BISP is targeted only to the poorest 15‐20 percent ofhouseholdsinPakistan.WespecificallyinterviewedBISPbeneficiariesandnon‐beneficiariesabout the program in order to explorewhat role it could play in any alternative energyaffordabilitypolicy.

Respondents overall demonstrated a high level of awareness of BISP. Low‐incomehouseholds in particular were aware of BISP’s eligibility criteria and applicationrequirements,sincemosthadparticipatedinthe2010NSERsurvey(fromwhichmostBISPbeneficiarieswere selected). BISP beneficiaries consider the cash assistance an essentialelementoftheirincomethathelpsthemaffordtheirutilitybills.Around70percentofBISPbeneficiaries interviewedperceived the applicationprocedure and the amountofmoneyreceivedasfair.

A considerable number of non‐BISP beneficiaries in the low‐income group, on the otherhand,feltthattheyshouldhavebeenselectedandreportedconcernsabouttheclarityandfairness of BISP selection procedures. These respondents expressed their desire foradditionalsupportmechanismsthatcouldhelpthemwiththeirenergyexpenses.

Box 3: In‐Depth Interviews with Service Providers 

According to a meter reading supervisor at PESCO, in Lower Dir district of KPK, meter readers face challenges during meter reading and bill distribution due to a shortage of field workers and difficulty reaching remote areas. Due  to  the  limited  number  of  staff,  the  company  could  not  deliver  bills  on  time  to  such  areas.  This  has consequences for the customers: 

“Just two or three days have been given to us for the distribution of bills. Because of the limited time frame we cannot reach bills to all people, and thus some people get their bills after the due date for bill payment. As a result they have to pay extra surcharge and fines.”  (Meter reader supervisor, Lower Dir, KPK) 

The supervisor also emphasized that there is a tension between meter readers and communities. He said that there have been instances in which consumers threatened meter readers over higher bills. 

A sub‐division officer at PESCO observed that meter readers are often accused of unfair readings. He mentioned that the manual meter reading system needs to be replaced with a new system. According to sub‐division officers in his area, there are more than 30,000 customers, but his staff checks only 6,000 to 7,000 meters a month. The remaining households receive estimated bills. 

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We asked respondents to choose their preferred energy affordability policy from threeoptions: (i) increasing the BISP cash transfer; (ii) implementing targeted concessionalpricing for the poor; and (iii) providing grants for energy saving measures. The mostcommonresponse(with87percentsupport)wastargetedconcessionalpricingforthepoor.Therewasaprevailingperceptionamongtheresearchparticipantsthatwell‐offhouseholdsgetcheaperelectricity,whichshouldbeaddressedthroughcredibleandimpartialtargetingof assistance.Respondents agreed thataddinganamount toBISPwouldhelpvulnerablehouseholds with their electricity expenses; however, there was a broad feeling that thebenefit would not help many needy low and lower middle‐income households that areexcludedfromthescheme.

AwarenessandAcceptanceofEnergyReforms

Finally,weaskedparticipantsabouttheplannedreformstosubsidies,andunderwhattermstheywouldacceptpriceincreases.Ingeneral,respondentswereunawarethattherewereelectricitysubsidies,especiallygiventhatelectricitypriceshave increased in the last fewyears.Womenweremoreawareofpriceincreasesthantheirmalecounterpartsastheyareheavilyaffectedbyeffortstoaffordelectricity.However,womenwerelessinformedaboutthereasonsforenergysectorreforms.Theyexpressedabeliefthattheincreaseinpricesisassociatedwithpoorgovernmentpoliciesandgovernance issuesinthesector.Consumerattitudestowardsreformsarealsoinfluencedbytheirtrustinenergysectorinstitutionsandtheirinteractionswithelectricityserviceproviders.

Box 4: Ethnographic Interview II 

General information about the household  There are eight members in the household. The respondent‘s husband is the main earner in the household and he works as a  farmer. They  live  in a house  in  the  countryside and have a  separate meter. They mainly use electricity for lighting, running fans and electrical appliances such as the fridge. They are not receiving any social assistance. 

Expenditures on energy sources  The respondent stated that at times the electricity bill seems too high. She believes that the high electricity bill is not plausible given excessive load shedding for several hours daily.  

Coping mechanisms  High electricity bills cause the household a great deal of stress. Due to inflation it is difficult to manage household expenses  including  food  and  the  children‘s  education.  The  family  tries  to  reduce  food  and  clothing  related expenses to pay their electricity bills. They also try to stay in one room to save energy and tend to sleep outside at night to avoid using fans. Despite these measures, they receive high electricity bills and are unable to pay. The respondent also added that friends and relatives had their own expenses and no one will lend them money.  

Attitudes toward energy reforms  The respondent has general knowledge about reforms, and has noted the gradual increase in electricity tariffs over the last five years. She does not have any interaction with WAPDA and mostly her husband deals with such matters. The respondent did not know the location of the electricity complaint office, nor the process of lodging complaints. She believes that it is government‘s responsibility to fix tariffs according to people‘s economic status.  

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Participantsperceivefuturepriceincreasesasunjustifiedwithoutimprovementsinservicereliabilityandquality.Mostoftherespondents—inparticular,BISPbeneficiariesandkatchiabadiresidents—mentionedthattheycouldnotbearfurtherincreasesinelectricitytariffs.Uponfurtherprobing,intervieweesagreedthatpriceincreaseswouldbeacceptableonlyifbills aremade credible, load shedding is reduced and governance issues are addressed.However,themajorityofhouseholdsvoicedtheirskepticismduringthediscussionsastheydoubtthatsuchimprovementswilleverhappen.ThiscontrastswithfindingsfromtheSDPIstudy,inwhich63percentofrespondentsindicatedthattheywouldbewillingtoacceptaRs.100‐500increaseintheirutilitybillsiftheywereprovided24hoursofuninterruptedservice.WhenaskedwhethertheywouldbewillingtopayanincreasegreaterthanRs.500,only19percentofrespondentsagreed.SDPIreportedthatallrespondentswouldacceptanincreaseinelectricitychargesifitwasguaranteedthattherewouldbenoloadsheddinginthefuture(SDPI,2014).

V. PolicyRecommendations

Movingbeyondgeneralpricesubsidies

Aswehavedemonstratedthroughoutthispaper, theexistingprice‐basedsubsidyfailstoprotect low and middle‐income households from high electricity costs whiledisproportionatelybenefitingrichhouseholds.Price‐basedsubsidieswillonlyfavorthepoor

Box 5: Ethnographic Interview III 

General information about the household There are eight members in the respondent’s household. They live in a semi‐structured house in a village. The respondent‘s husband works at a hotel, while she manages the household. They have six children, and all of them are  school age. The household  shares an electricity  connection with  relatives, and  the monthly bill  is divided equally. 

Expenditures on energy sources  The household spends Rs. 300 to 700 per month on electricity and Rs. 200 to 300 each month on alternative energy sources such as candles. The family collects its electricity bills from the local village mosque, and the men pay the bills. The respondent tries her best to pay the bills on time given the bill is shared with her relatives. If there are any delays in payment, her relatives pressure her and this leads to tension.  

Coping mechanisms  The respondent generally pays her bill on time. There was only one time when she had to take a Rs. 300 loan from her sister to pay her bill. However, her husband  is sick, and even small bills are difficult to afford. Any increase  in cost of electricity would affect the monthly budget.  It  is not easy for her to send her children to school since the family struggles to afford food.  

Social assistance  The respondent’s family has received Rs. 1,500 monthly from BISP for the last three years, and this has been very useful in helping her afford her electricity costs. Her household uses the BISP cash mainly for food and the children‘s education. She has also managed to put aside some money for emergencies. 

Attitudes toward energy reforms  The respondent stated that she does not have sufficient knowledge regarding the reforms in the energy sector. In her opinion, the government is responsible for making such decisions. However, she was aware that the price of electricity had been increasing. 

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ifrecordedelectricityconsumptioniscloselytiedtooverallwelfare.This isevidentlynottrue in the caseofPakistan—eitherbecauseelectricityusagepatterns are similar acrosshouseholds, or because the current system of metering does not accurately captureconsumption. Seasonal fluctuations further distort the functioning of subsidies, exposingpoor households to higher per‐unit costs for electricity in the summer, when theirconsumption is highest, andprovidingunwarranted assistance to rich households in thewintermonths.Toaddressthesedrawbackswiththepresentsystem,inthissectionwelookathowtargetingcanbeimproved,andhowtomakeenergyaffordablewhileencouraginguserstostaywithintheformalsystem.

Improvedtargeting

Itisevidentfromtheelectricityconsumptionanalysisthatprice‐basedsubsidiesarenotaneffectivemeansof targetingassistance to thehouseholds thatneed it themost. Pakistanalreadyhasademonstrablybettertargetingmechanism.TheNSERcontains‘povertyscores’foralmostallhouseholdsinthecountry,effectivelyrankingthemfrompooresttorichest.Theregistry,indexedbyCNICnumber,isalreadyusedfortargetinginover30programsinPakistan.TheNSERallowsthegovernmenttoselectanysubgroupofthepopulationbasedon their welfare level; therefore assistance could be directed to any subgroup of thepopulation.

The matching exercise conducted for this paper was in effect a preliminary test of theapplicabilityofthistargetingmechanismtoelectricitysubsidies.UsingtheCNICrecordsintheDISCObillingdatabases,NADRAwasabletomatchpovertyscorestoalmosthalfofthe350,000households.ThematchrateisimpressivegiventhattheNSERwasconstructedin2010andmanyhouseholdsdidnothaveaCNICatthetime.AhighermatchratecouldbeachievediftheNSERisupdated,anexercisewhichtheGovernmentofPakistaniscurrentlyundertaking.Tobesurethatrecordscanbematched,householdscouldberequiredtoreportinpersontotheDISCOofficewiththeirnationalIDcardandarecentelectricitybill.Theywould identify themselvesusing thebiometrics stored in thecard,and theCNICnumberwouldbeusedtolookuptheirpovertyscoreandmakeaninstantdeterminationofeligibilityforassistance.15Forrenters,atenantwouldbeentitledtoclaimasubsidyevenifthebillisinthenameofalandlord,butthesubsidywouldbelimitedtooneperfamily,withfamiliesencouraged to re‐register at their new address if theymove. NADRA could provide thetechnicalsupporttoimplementsuchatargetingsystemthroughDISCOofficesoranothergovernmentpost.To limitsubsidies tooneper family,acentraldatabaseofbeneficiarieswouldneedtobedeveloped.

A simpler alternative, whichmightworkwell if the objective is to eliminate the richesthouseholdsonly,wouldbetoapplyexclusionfilterstodetermineeligibility.Forexample,householdswithregisteredland,payersofincometax,holdersofbankaccounts,andsoon,couldbeidentifiedbyCNICandexcludedfromthebenefit.Furtheranalysiswouldbeneeded

15NADRAhasthecapacitytoaccesstheNSERdatabaseinrealtime,andtheCNICisequippedwithbiometricidentificationcapabilities.

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tobetterunderstandwhichhouseholdswouldbeexcluded,andwhethertherewouldbeanydeservinghouseholdsundulyimpactedbythisapproach.

Withanytargetingmechanism,itisimportanttohaveaveryclearprocessofapplication,review,appeal,andfinaleligibilitydetermination.Thistouchesontwoissuesinparticular:the need for a grievance redress mechanism; and the need for a carefully designedcommunicationspolicy.Bothissuesarediscussedinfurtherdetailbelow.

Affordabilitymeasures

Theexistingsubsidystructurecouldbemaintainedforeligiblehouseholdsonly;ineligiblehouseholdscouldbechargedtheNEPRA‐determinedtarifforanothercost‐neutralpricingformula.However,suchasystemwouldnotbefullyequitable,andwouldnotdealwiththeseasonalityissue.Analternativeapproachwouldbetoreplacesubsidieswithabillcredit,chargingallhouseholdsacost‐recoverytariffandapplyingamonthlycredittothebillsofeligible households. The credit could be set at an amount equivalent to basic electricityneeds,withthehouseholdpayingforusageabovethislevel.Theamountofthecreditwouldtherebyvarywithtariffs.Thecreditwouldserveasavisible‘subsidy’fromthegovernment,incontrasttothemoreopaqueimplicitpricesubsidiesprovidedcurrently.Toaddresstheseasonality issue, any unused portion of the credit could be rolled over to subsequentmonths(withsomecap),sothathouseholdsnotusingalloftheircreditinthewintercouldsavetheremainderforthesummermonths.

Wealsorecommendthatthegovernmentconsidermoreflexibleoptionsforpaymentofbills.Ourqualitativeanalysisfoundthatpoorerhouseholdsarevulnerabletounexpectedshocks,suchasillness,thatmaymakepayingelectricitybillsdifficult.Somereportedthattheyweredisconnectedasaresult,andturnedtothekundasystem.Allowingflexiblerepaymentwouldreducepressuresoncustomerstobribeofficialsormovetokunda.Itwouldalsohelpverypoorhouseholdstosmooththeirconsumptionandavoidresortingtosellingassetsorgoingintodebt.Householdscouldbeprovidedwithalow‐interestrepaymentoption,orgivenalongerperiodoftimetorepaytheirbill.Penaltiesforlatepaymentcouldalsobewaivedforhouseholdsinthetargetgroup.Suchpolicieswouldneedtobedesignedcarefullytoavoidmoral hazard issues, but would be a way of recognizing the vulnerability of poorerhouseholdstorisingenergycosts.

OneofthemainlimitationsoftheaboveformsofassistanceisthattheyexcludehouseholdswhoarenotformallycustomersoftheDISCOs—agroupthatincludesmanyofthepoorestandmostphysicallyisolatedhouseholdsinPakistan.These‘unconnected’householdscanbebroken into three groups: (i) households living outside the service area; (ii) householdsliving in service areas but not (formally) connected to the grid; and (iii) householdsconnectedtothegridthroughanillegalconnection(suchaskunda).Forhouseholdsoutsidethe service area, there is no straightforward solution other than gradual expansion ofcoverage. In the meantime, the government may consider providing other forms ofassistancetothesehouseholdstohelpthemcovertheirenergycosts.Forthoseinsidetheservicearea,somecouldbeencouragedtoconnecttothegridbyofferingawaiveroftheconnection fee. For those who are connected illegally, an amnesty and waiver ofreconnectionfeecouldbeprovidedforalimitedtimetoenticethesecustomerstoresume

20

anofficialaccount,whilethebillcreditandmoreflexiblepaymentoptionsproposedabovewouldhelpthempaytheirbillsandstayconnected.

Ensuringthesuccessofthereform

Internationalexperienceillustrateshowcountriesthatsucceededinreformingsubsidiesdidsobyaddressingissuesofconcerntothepublicthroughaclearcommunicationscampaign,andthroughcarefulsequencingofthereform.

Packagingthereform

Thequalitativeanalysisshowsthatconsumersareprimarilyconcernedaboutaffordability,reliabilityofsupply,andissuesrelatedtotransparencyandaccountability.Toconvincethepublic,thereformshouldaddresseachoftheseissueswithaclearplanofactionandtimelineforresults.Affordabilitycanbeaddressedintheneartermbyintroducingmoregenerouscompensation mechanisms targeted to a subset of the population that genuinely needsassistance.Inthelongerterm,affordabilityandreliabilityofsupplycanbeimprovedthroughinvestmentininfrastructureandbettergovernance.Concreteactionscanalsobetakentoimprove transparency and accountability, especially relating to the billing system andresolutionofgrievances.

Consumers do not trust the accuracy of their bills, and perceive corruption in theirinteractions with service providers. Investment in capacity to read meters and clearerpresentationof thebills themselves isaknownpriority,andthegovernmenthasalreadytakenactioninthisregard.Householdsalsoreportfeelingunabletoasserttheirrightsasconsumers. DISCOs in Pakistan have customer service mechanisms in place, includingdedicatedcustomerservicecenters,websitesforlodgingcomplaints,callcentersandSMSservices (Table 3). These mechanisms could be strengthened to effectively and rapidlyrespondtoqueriesandcomplaints.ThegovernmentcouldencourageDISCOstoexperimentwiththesetechniquesbyrewardingthebestperformersandpublicizingtheirapproaches.

Thegovernmentcouldalsoputinplaceorstrengthengrievanceredressmechanisms(GRMs)andprovidetrainingtostafftoaddressconsumerconcernsinamannerthatbuildstrust.AGRMwillbeessentialtomanagethetransitionawayfromuniversalsubsidies,andtodealwith appeals to selection decisions under a new targeting method. Box 6 provides anexampleofhowtheGRMcouldbedesigned.Multipleimplementationpartnersmayneedtoplay a role in redressing grievances: identity verification grievances handled byNADRA,billingdatagrievancesbyDISCOs,andeligibility/targetinggrievancesbyBISP.

Tofurtherstrengthencitizenengagement,a‘socialcompact’approachcouldbeadopted.Asocialcompactisaformalarrangementinwhichtheviewsofcitizensaresoughtatregularforumsat the local level, andactively incorporated inpolicymaking.The social compactapproachaimstoincreasemutualtrustandaccountabilitybetweenserviceprovidersandconsumers through stakeholder consultations and participatory monitoring. The socialcompactapproachwasimplementedintwoprovincesinSoutheasternAnatolia,Turkey—the region with the highest nonpayment rates in the country. Stakeholder committeesrepresentingconsumersandtheelectricitycompanywereestablished.Thesecommittees

21

developedajointplantoaddresspayment,servicequality,andcommunicationissues.Theelectricitycompanyagreedto institutionalizethisplanandimproveitsgrievanceredressmechanism.Inreturn,citizenswereexpectedtoincreasepaymentrates.Thisapproachmaylikewise be a good way of increasing trust and mutual accountability between serviceproviders and consumers in Pakistan, especially in areas where illegal electricity use iscommon.Indeed,KarachiElectrichasalreadyhadsuccessfulexperienceapplyingsuchanapproachinsomeofitsserviceareas.

CommunicationandSequencing

Lackofawarenessandmisinformationcanbeoneofthebiggestbarrierstosubsidyreform.AstudybytheIMFindicatedthatin22casesofreform,lackofacommunicationplanwasthe biggest cause of failure (Clements et al., 2013b). Information campaigns haveunderpinned the success of reforms in a number of countries, including Armenia (ibid),Indonesia (World Bank, 2011), the Islamic Republic of Iran (IMF, 2013b) and Uganda(Sdralevichetal.,2014).InthecaseofPakistan,theinformationcampaignshouldbothmakethecase for thereform,andeducateeligiblehouseholdsabouthow toapply for thenewbenefits.Thecampaigncouldincludepublicaddressesbyseniorgovernmentofficials,mediacampaigns,focusedoutreachactivities,andinclusionofcivilsocietyandotherstakeholders.Thecommunicationagendashouldcontinuethroughoutthereformprocess,andshouldbelaunchedbeforethereformsbegin.Thecommunicationstrategyshouldtakeintoaccountthe interests of various stakeholder groups (World Bank, 2015). Beyond the traditionalmedia, interpersonalchannelscouldbetapped,suchascommunity influencers,mosques,representatives of the localUnionCouncils, and community outreach. Thismaybemoreeffective in reaching poorer households: a recent survey found that among BISP

Box 6: Example of a Successful GRM: The Pakistan Flood Emergency Cash Transfer Project 

The cash  transfer program  for  the Pakistan Flood Emergency project had a very successful grievance  redress mechanism  (GRM). The GRM  included  facilitation  centers with grievance  redress  counters.  It also  included a public information campaign on the grievance redress process. Television, radio, print, and word‐of‐mouth were used as part of the communication strategy. In addition to facilitation centers, complaints could be registered by text messages, phone and calls. The project successfully mobilized different organizations to address different types of grievances, for example NADRA centers handled grievances related to incorrect personal details and local authorities dealt  cases of  eligibility/targeting  grievances. Hotlines were  created  to handle  cases of  incorrect personal details. The local authorities checked whether the applicant is based in a flood‐affected area and if they have already received the benefit. Another channel of communication was through local influential leaders who could verify the applicants’ status as flood affectees. The district authorities supervised the review process and the eligibility statuses were submitted to the Provincial Disaster Management Authority (PDMA). The final step involved NADRA entering the decisions into case management systems and clearing the households enrolled at the facilitation centers. For the payment grievances, the partner commercial banks operated through offices and dedicated hotlines. Grievances related to maladministration and unaddressed complaints were handled by the District Administration or NADRA. The GRM successfully handled grievances and has been cited as one of the most effective GRMs for emergency projects in Pakistan. The example shows that an effective GRM is one that is efficient on multiple fronts and where each organization effectively handles grievances both individually and as part of the collective effort. 

Source: Rao, 2014. 

22

beneficiaries, 58 percent relied on mosque announcements for information, 47 percentreliedonTV,andonly10percentmentionedradioornewspaper(MottMcDonald,2014).

VI. Conclusion

AlthoughelectricitysubsidieswereintroducedasaformofsocialsafetynetinPakistan,theanalysisofhouseholdsurveyandbillingdatainthispaperdemonstratesthattheycontinuetobe regressively targeted,and thatmanypoorhouseholds remainexposed tohighbillsespeciallyinthesummermonths.Subsidiesareoftenintroducedinthenameofhelpingthepoor,butimplementedinisolationfromothersocialprotectionprograms,mainlyduetothemappingof implementationresponsibilitieswithingovernment.Going forward, subsidiesandtheirreformsshouldbepartofthebroaderdialogueonsocialprotectioninPakistan,andconsideredasoneofasetofantipovertyinterventions.

Thequalitativeassessment findings indicate thatelectricity is central to the livesof low‐incomeandlowermiddleincomehouseholdsandthathouseholdsstrugglewithelectricitycostsandtheyresorttocopingmechanismssuchasreducingnecessaryexpensesonfood,health and child care to affordelectricitybills. Low‐incomehouseholds, especiallykatchiabadiresidentsandBISPbeneficiaries,useillegalelectricity(calledthekundasystem)asawaytocopewithincreasingelectricitycosts.Despiteeffortstoimproveservicedelivery,loadsheddingandelectricityoutagesstillnegativelyimpactonhouseholds’economicandsocialwell‐being.Womenaremoreaffectedby loadsheddingandby thehousehold’sefforts tomanage electricity expenses because they are on average the main users of electricalappliancesandspendmoretimeinthehome.Themajorityofconsumersdonottrusttheirbills,andbelievethattheirbillamountsdonotreflecttheiractualconsumption.Almostnoneoftherespondentswereawarethatthegovernmentprovideselectricitysubsidies.Overall,thenegativeattitudeofrespondentstowardtheelectricityserviceisaresultoffrustrationwith unreliable supply and perceptions of poor sector governance. Despite struggling toaffordelectricity,respondentsappearwillingtopayhigherpricesprovidedservicequalityimproves and governance problems are addressed. However, most respondents areskepticalthatsuchimprovementswilltakeplace.

When governments undertake subsidy reforms, they have two main levers to helphouseholdsadapttohigherprices:(i)compensatinghouseholdsforthepriceincrease;and(ii) encouraging households to adjust their consumption patterns (Yemtsov et al.,forthcoming).Inthisanalysiswehavefocusedontheformer,andillustratedhowPakistancan better cushion the effect of energy price fluctuations on poor and economicallyvulnerablefamiliesbytargetingcompensationusingtheexistingNSERdatabase.However,apilotwouldbeneededtoexaminethecost‐effectivenessoftheapproachgiventhecostsofimplementation.

References

Beaton,C.andLontoh,L.2010.“LessonslearnedfromIndonesia’sattemptstoreformfossil‐fuelsubsidies,”Internationalinstituteforsustainabledevelopment(IISD).Trade,InvestmentandClimatechangeseries.

Clements,D.C.,Benedict,J.,Fabrizio,S.,Gupta,S.,Alleyne,T.andSdralevich,C.A.2013a.“EnergySubsidyReform:LessonsandImplications.”InternationalMonetaryFund:Washington,DC.

Clements,D.C.,et.al,2013b.“Casestudiesonenergysubsidyreform:lessonsandimplications.”InternationalMonetaryFund:Washington,DC.

Coady.D.,Parry,I.,Sears,L.andShang,B.2015a.“HowLargeAreGlobalEnergySubsidies?”IMFWorkingPaperWP/15/105,Washington,DC.

Faisal,J.andEatzaz,A.2014.“AnEmpiricalStudyofElectricityTheftfromElectricityDistributionCompaniesinPakistan.”PakistanDevelopmentReview.

GovernmentofPakistan,MinistryofWaterandPower.2013“NationalPowerPolicy.”Availableat:http://www.ppib.gov.pk/National%20Power%20Policy%202013.pdf

InternationalMonetaryFund(IMF).2013a.“Pakistan:StaffReportforThe2013ArticleIVConsultationandRequestforanExtendedArrangementUndertheExtendedFundFacility.”Availableat:https://www.imf.org/external/pubs/ft/scr/2013/cr13287.pdf

InternationalMonetaryFund(IMF).2013b.EnergySubsidyReform:LessonsandImplications.WorkingPaper,January28,2013.

Imtiaz,S.andur‐Rehman,Z.2015.“DeathTollFromHeatWaveinKarachi,Pakistan,Hits1000.”NewYorkTimes.June2015.Availableat:http://www.nytimes.com/2015/06/26/world/asia/karachi‐pakistan‐heat‐wave‐deaths.html

MottMacdonald.2014.‘BISPSpotCheckandBeneficiaryFeedback‐NationalCashTransferProgramme’,Volume1.

O’Leary,S.,Cheema,I.,Hunt,S.,CarraroL.andPellerano,L.2011.‘BenazirIncomeSupportProgrammeProgramEvaluation,BaselineSurveyReport.’OxfordPolicyManagementInstitute,2011.

Rao,S.2014.‘GrievanceRedressMechanismsinPakistan.’GSDRC.http://www.gsdrc.org/docs/open/hdq1117.pdf

Sdralevich,C.,Sab,R.,Zouhar,Y.andAlbertin,G.2014.SubsidyreformintheMiddleEastandNorthAfrica:Recentprogressandchallengesahead.InternationalMonetaryFund:Washington,DC.

24

SustainableDevelopmentPolicyInstitute.2014.“Energy&TaxReforms:HouseholdAnalysisfromPakistan.”Islamabad:SustainableDevelopmentPolicyInstitute.

Walker,T.,Sahin,S.,Saqib,M.andMayer,K.2014.“ReformingElectricitySubsidiesinPakistan:MeasurestoProtectthePoor.”Washington,DC:WorldBank.

TheWorldBank.2011.Indonesia:CommunicationsStrategytoSupportFuelSubsidyReformandEnsuingCashTransfer.Washington,DC:WorldBank.

TheWorldBank.2015.“TowardGender‐InformedEnergySubsidyReforms:FindingsfromQualitativeStudiesinEuropeandCentralAsia”.Washington,DC:WorldBank.

TheWorldBank,OECD&OPEC.2010.“Aroadmapforphasingoutfossilfuelsubsidies,”TheWorldBankGroup’scontributiontothe2ndIEA,WorldBank,OECDandOPECJointReport,preparedforsubmissiontotheG20summitmeetinginSeoul,11‐12November2010.

Yemtsov,R.,etal.Forthcoming.“SocialSafetyNetsandPoliticalEconomyofEnergySubsidiesReform:AGuidebookforPractitioners”.SocialProtectionGlobalPractice.TheWorldBankGroup:Washington,DC.

25

Table1:ResidentialelectricitytariffschedulesMonthlyconsumption(kWh) 2012‐13 2013‐14 2014‐15 2015‐16

0‐50* 1.87 2.00 2.00 2.001‐100** 4.54 5.79 5.79 5.79101‐200

6.868.11 8.11 8.11

201‐300 8.11 12.09 10.20301‐700 10.65 12.33 16.00 16.00700+ 13.29 15.07 18.00 18.00

Note:*Lifelinerateforconsumersbelow50kWh/month.Seealsofootnote2.**Consumersabove50kWh/monthpaythisrateforthefirst100units.

Table2:SummaryofhouseholdcharacteristicsandelectricityconsumptionbyPMTquintile

QuintileofPMTdistribution

Medianhouseholdsize

Mediannumberofhouseholdmembersper

room

Medianelectricity

consumption(kWh/month)

Meanelectricityconsumption(kWh/month)

Poorest 7 6 81 92Lower‐Middle 6 4 94 101Middle 5 3 102 110Upper‐Middle 4 2 100 109Richest 5 2 118 133

Table3:DISCOcustomerservicemechanisms

DISCO Customerservicecenter

Complaintsonwebsite

Callcenter Complaintsvia

SMS/Phone

Onlinebillpayments

IESCO LESCO GEPCO FESCO PESCO HESCO MEPCO SEPCO K‐Electric

26

Figure1:Currentpriceandsubsidystructureforresidentialsubsidies,2014‐15

Note:CostisthenationalaverageNEPRA‐determinedtarifffortheslab.

Figure2:Residentialelectricityexpenditurebydecileofper‐capitaconsumption

(BasedonPSLM2013‐14data)

Source:StaffcalculationsbasedonPSLM2013‐14data.

0

300

600

900

1200

1500

1800

0

3000

6000

9000

12000

15000

18000

0 100 200 300 400 500 600 700 800 900 1000

Rs

Monthly Consumption (kWh)

Rs

Total cost(left axis)

Total tariff(left axis)

Total subsidy(right axis)

0%

20%

40%

60%

80%

100%

Lifeline(0‐50) 50‐100 100‐200 200‐300 300‐700 700+

Poorest RichestDecileofper capitaconsumptionin2013‐14

kWh/mth

27

Figure3:Illustrationofmatchingprocess

Note:NumbersforeachrecordaretheCNICnumbersforthebill‐payer(DISCOdatabase)andhouseholdhead(NSERdatabase),whichcanbereconciledasshownusingthefamilyfolder(listofallCNICsoffamilymembers)asshowninthediagram.

Figure4:DistributionofmeanmonthlyelectricityconsumptionofhouseholdsinGEPCO,FESCOandIESCOserviceareas,2013‐14

(ByPMTscoredecileandtariffslab)

Source:StaffcalculationsbasedonmatcheddatafromGEPCO,FESCOandIESCOconsumersfor2013‐14.

0%

20%

40%

60%

80%

100%

1 2 3 4 5 6 7 8 9 10

0‐50(LIFELINE) 50‐100 100‐200 200‐300 300‐700 700+

Poore RicheDecile ofPMTscore

kWh/mth

NADRA Family Folder 

1014455407970 

1014628567800 

1016026187900 

1110115162273 

1110145063983 

DISCO Database 

1014455407970 

1120103884459 

1110145063983 

1140532444124 

1197818458200 

NSER Database 

Direct match 

1120103884459 

1014628567800 

1120145728065 

Indirect match 

28

Figure5:Distributionofsubsidies,2013‐14ByslabandPMTquintile

Source:StaffcalculationsbasedonmatcheddatafromGEPCO,FESCOandIESCOconsumersfor2013‐14.

Figure6:SeasonalVariationinElectricityConsumption,2013‐14ByPMTquintile

Source:StaffcalculationsbasedonmatcheddatafromGEPCO,FESCOandIESCOconsumersfor2013‐14.Note:Linesshowcumulativeshareofhouseholdsbyquintileandquarter.Q1:July‐September2013,Q2:October‐December2013,Q3:January‐March2014,Q4:April‐June2014.

0

50

100

150

200

Poorest20% Lower‐Middle Middle Upper‐Middle Richest20%

0‐50 50‐100 100‐200 200‐300 300‐700 700+

Rsm

0%

20%

40%

60%

80%

100%

0%

20%

40%

60%

80%

100%

Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4

Poorest 20% Lower‐Middle Middle Upper‐Middle Richest 20%

0‐50 (Lifeline) 50‐100 100‐200 200‐300 300‐700 700+

29

Figure7:Electricityusebyapplianceandrespondenttype

Source:Authors’calculationsbasedondatacollectedonparticipantsinqualitativestudy.

Figure8:Copingmechanisms

Source:Authors’calculationsbasedondatacollectedonparticipantsinqualitativestudy.

0 10 20 30 40 50 60 70 80 90 100

Fans

Mobile chargers

Iron

Washing mach

Water motors

TV

Fridge

Sewing machines

Heating rod

Fodder cutters

Computers

Juicers&mixers

AC

Katchi abadi

BISP beneficiaries

Rural

Urban

%

0% 20% 40% 60% 80% 100%

Cut other expenditure

Borrow from friends/relatives

Pay bill in installments

Sell assets or livestock

Kunda (illegal connection)

Reduce energy use

Work additional jobs Lower middle income

Low income + mixed income

BISP beneficiaries

Katchi abadi

30

Figure9:PercentageofFGDparticipantsperceivingtheirbillsasinaccurate

Source:Authors’calculationsbasedondatacollectedonparticipantsinqualitativestudy.

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Katchi abadies

Lower middle urban

Lower middle rural

BISP

Mixed urban

Low income urban

Low income rural

31

Appendices

A. Detailsofthematchingprocessforbillingdataanalysis

TableA1:DomesticconsumersineachoftheDISCOsDISCO Totalcustomers Shareofnational

consumptionGEPCO 2,487,990 12.5FESCO 3,004,486 15.1IESCO 1,983,613 10.0Total 7,476,089 37.6Source:MinistryofWaterandPower(June2015)TableA2:SuccessrateofmatchingconsumptionCNICswithpovertyscores

DISCO CNICsprovidedbyDISCO

MatchedtoNSER

NotmatchedtoNSER

Proportionmatched(%)

GEPCO 132,388 60,653 71,735 45.8IESCO 47,463 24,016 23,447 50.6FESCO 146,075 61,410 84,665 42.0Total 325,926 146,061 179,865 44.8FigureA1:Domesticconsumptionpatterns,2013‐14

ThevariablesmatchedthroughCNICwithNSERrecordswere:1. Povertyscore

2. Householdcomposition(numberofchildren,numberofadultsinthefamily)

3. GenderofCNICholder

Up to 50

51‐100

101‐200

201‐300

301‐700

Above 700

Billing Data Sample

Up to 50

51‐100101‐200

201‐300

301‐700

Above 700

All DISCOs

32

4. AgebracketofCNICholder

5. Disabilitystatusofthehouseholdhead

6. Employmentstatusofthehouseholdhead

7. Educationlevelofthehouseholdhead

8. Numberofrooms

9. Electricappliancesowned16

10. Livestockowned17

AqueryoftheNSERdatabasewasruntomatchtheCNICsinthebillingdatawiththeCNICsin theNSERdatabase.The two‐stepmatchingprocesswasdesigned toget themaximumnumber of CNICs fromDISCOsmatchedwith theNSER CNICs so that a poverty score isrecordedfortheanalysis.ThefirststepwastodirectlymatchtheDISCOCNICwiththeNSERdatabaseandthesecondstepwastomatchtheDISCOCNICthroughafamilymember’s‘alphafamily’18intheNSER.Thissecondstepwasdesignedtoachievemaximumresultsfromthematchingprocess.NADRAmatchedtherecordsbyCNICnumber,acommonvariableinbothdatasets.Around45%oftheCNICsweresuccessfullymatchedwiththePMTscores.FESCO,GEPCOandIESCOhaveupdatedconsumerCNICrecords.EachoftheseDISCOshasadifferenttimeframeforupdatingtheirCNICrecords;IESCOupdatesitsrecordseachyearwhileFESCO&GEPCOlastupdatedtheirrecords2‐3yearsago.TableA3:FrequencyofCNICsindatabase

16Electricequipment:washingmachine,refrigerator,AC,cookingrange,microwave,geyser,cookingstove,cookingrange,TV,aircoolerandheater.17Livestock:Sheep,bull,cow,buffaloandgoat18AlphafamilyisatermusedbyNADRAwhichincludesparentsand/orspouseandchildrenoftheperson.

Column1 Sample % of Sample

Total DISCO CNICs 381907 100

Single meters 317140 83

2 meters 17630 5

3 meters 4842 1

More than 3 meters 42289 11

33

B. DistributionofSubsidybyPovertyStatus

TableB1:Totalsubsidybypovertygroup

TableB2:Consumptionbyquintileandslab

TableB3:AverageTDSinFY14

0‐50(Lifeline

) 50‐100 100‐200 200‐300 300‐700 700+NEPRADeterminedTariff(PKRperunit) 4 11.8 14.39 14.39 16.25 17.85GOPNotifiedTariff(PKRperunit) 2 5.79 8.11 12.09 16 18TDS(PKRperunit) 2 6.01 6.28 2.3 0.25 ‐0.15Note:TDS=GOPNotifiedTariff–NEPRADeterminedTariff

0‐50 50‐100 100‐200 200‐300 300‐700 700+

First quintile 29214.0 17.5 48.8 39.4 9.7 1.0 ‐0.1 116.4 3983.1

Second quintile 29800.0 16.4 53.6 49.4 12.9 1.2 ‐0.1 133.4 4477.2

Third quintile 28641.0 14.5 54.3 55.1 15.7 1.3 ‐0.1 140.8 4915.6

Fourth quintile 29196.0 15.2 53.6 54.5 15.7 1.3 ‐0.1 140.2 4800.4

Fifth quintile 29209.0 12.2 56.8 67.9 24.6 2.0 ‐0.2 163.3 5590.6

Number of 

households Total subsidy Subsidy per HHQuintile of poverty score

Subsidy received by slab

None 0‐50 50‐100 100‐200 200‐300 300‐700 700+

First quintile 29,214 566 8,854 7,980 9,873 1,540 386 15

Second quintile 29,800 546 7,998 7,338 11,224 2,127 551 16

Third quintile 28,641 546 7,143 6,462 11,082 2,609 783 16

Fourth quintile 29,196 562 7,672 6,533 10,939 2,624 844 22

Fifth quintile 29,209 508 6,323 4,935 11,468 4,176 1,741 58

By quintile of poverty score

Number of 

households

Average electricity consumption (kWh/mth) for 2013‐14

Subsidized Unsubsidized

34

C. SampleDistributionbyDistrict

TableC1:District‐wiserepresentationinbillingdatasample

DISCO DistrictShareofbillingdatasample(%)

IESCO Attock 4

FESCO Bhakkar 2

IESCO Chakwal 1

FESCO Faisalabad 14

GEPCO Gujranwala 8

GEPCO Gujrat 10

GEPCO Hafizabad 2

IESCO Islamabad 2

FESCO Jhang 8

IESCO Jhelum 1

FESCO Khushab 2

GEPCO MandiBahauddin 8

GEPCO Narowal 4

IESCO Rawalpindi 7

FESCO Sargodha 5

GEPCO Sialkot 7

FESCO TobaTekSingh 5

Others 10

Total 100

35

D. HomeOwnershipandRental

Ownshome? Rural Urban Total

Owner 92.5 72.0 84.7

Non‐owner 7.5 28.0 15.3

Source:Authors’calculationsbasedonPSLM2013‐14.Notes:Ruralpopulationshareis62%,urbanis38%.

36

E. PMTdistributioninbillingdatasample

TableE1:ComparisonofbillingdataPMTdistributionwithpopulationdistribution

TheplotshowsthedistributionofthePMTscoreinthesampleusedfortheanalysis(line),withthePMTdistributioninthefullNSERdatasetoverlaid(columns).TheNSERdatawassourcedfromaBISPinternalanalysispresentationentitled“PresentationtotheCabinetDivision,GovernmentofPakistan”(dated22March,2012).

0.0

1.0

2.0

3D

ensi

ty

0 20 40 60 80 100Poverty Score

kernel = epanechnikov, bandwidth = 1.2137

Kernel density estimate

37

F. FurtherDetailsontheQualitativeResearch

The qualitative research comprised 44 focus group discussions (FGDs), 16 follow‐upethnographicinterviews(EIs)withasingleparticipantfromthefocusgroup,and12in‐depthinterviewswithkeyinformants.ThebreakdownofFGD,EI,andIDIparticipantsisdescribedinTableF1.Focus group discussions were conducted with 8‐10 household heads or spouses,segregated by gender and stratified by socioeconomic status. The FGDs encouraged freediscussionofthefollowingtopics:1. Consumerbehavior

Electricityconsumptionpatternsofhouseholds; Themoststressfultimeswithrespecttoelectricitypayments; Theimpactofelectricitybillsandtariffincreasesonhouseholdbudgets; Methodshouseholdsusetocopewithtariffincreases—forexample,cuttingbackon

otherspending(andifso,whatexpensesarecut);and Gender‐specificimplicationsofanincreaseinelectricitytariffs.

2. Perceptionsofservicequality

Reliabilityandvalueformoneyoftheelectricityservice; Consumerexperiencesinteractingwithelectricityserviceproviders;and Concernsrelatingtoserviceproviders(includingclarityof tariff‐settingprocesses,

accountability,understandingofbilling,andtheftornonpaymentofbills).3. Attitudestowardsreformandcompensation

Awareness of, and attitudes towards, the government’s electricity sector reformagenda;

Conditionsunderwhichconsumerswouldbewillingtopaymoreforelectricityandpaytheirbillsontime;

Elementsthatshouldbeconsideredincommunicationeffortsaccompanyingenergyreforms;and

Perceptions of the most effective measures to protect poor households againstadverseimpactsofenergytariffincreases.

Ethnographicinterviewsfocusedonmorespecificinformationabouthouseholds’energycostsandthewaysinwhichtheyexperiencetheimpactsoftariffreforms.In‐depthinterviewswereconductedwithkeyinformantstogathertheiropinionsonthesame topics to validate, explain, and balance opinions expressed by households’ energyconsumers. Key informants interviewed included social assistance and energy companyrepresentatives.

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TableF1:QualitativeResearchSampleProvince District Locality Village/CommunityName Gender SocioeconomicGroup Ethnographic

interview?Serviceproviderinterview(IDI)

KhyberPakhtun‐khwa

LowerDir Urban QurataroMohallha,UCTimarGhara Male LowerMiddleIncome IDIwithBISPAssistantDirector

Rahimabad‐UC/Tehsil‐SamarhBagh Female LowerMiddleIncome ShahMohallaShakhans‐UC‐TimerGahara

Female Katchiabadi IDIwithlineman

Rural Rehmnabad,UCNooraKhal Male LowerIncome NageerPayeen Female LowerIncome

Manshera Urban Chennai‐UC3 Male LowerIncome NeighbourhoodNoGhaz1 Female LowerIncome CityNo‐NogaiNori,UC‐2 Male Katchiabadi

Rural Shamdara Male LowerMiddleIncome Behali,UCManshera Female LowerMiddleIncome IDIBehali,UCManshera Male BISP Shamdara/Tehsil‐Mansehra Female BISP IDI

Punjab Lodhran Urban MahmoodaAbad,UCGulabPura Male MixedIncome DuniaPur,UCGulabPura Female MixedIncome ShahMuhammadQabristan‐EidGahMohallah‐DuyinaPur

Female LowerMiddleIncome IDI

MohalaNokhalWala Female Katchiabadi Rural Chak231,Lodhran Male LowerIncome

UCGulabPuraBastisalsadar Female LowerIncome ChakNo‐237/WB Male LowerMiddleIncome IDISalSadar Male BISP IDIChakNo.237 Female BISP IDIwithBISP

AssistantDirectorMuzafargarh Urban WardNo10MohallaMochiwala Male LowerIncome

BastiDewanWala Female LowerIncome DarkhanWala,UCKhanGarh Female LowerMiddleIncome TibbaKareemWala Male Katchiabadi IDIwithlineman

Rural BastiKodaiwala,TehsilKotUddo(UCMinha)

Male LowerMiddleIncome

VillageGanga Female LowerMiddleIncome BastiHayatWalaMozaMunhaSharif,Darkhan

Male LowerMiddleIncome

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TableF1:QualitativeResearchSample(continued)Province District Locality Village/CommunityName Gender SocioeconomicGroup Ethnographic

interview?Serviceproviderinterview(IDI)

Sindh TMKhan Urban MizarBaraniMohalla,UC3 Male MixedIncome GulshanFaizColony,UC1 Female MixedIncome IDIPattarGoth,UC1 Male LowerMiddleIncome PattarKotUC1 Female LowerMiddleIncome GulshanFaizColony,MohallaSomra,UC1

Male Katchiabadi IDIwithBait‐ul‐malofficer

Rural UCAllah‐YarTurkVillage,MulaKatiyarandJamalShoro

Male LowerMiddleIncome

UCSyedPurVillage‐TakarMohalaMemon

Female LowerMiddleIncome IDI

KamisPur Male LowerMiddleIncome KamisPur,District–TandoMuhammadKhan,Sindh

Female LowerMiddleIncome

Nawabshah(Benazirabad)

Urban SachalColony–Benaziraabad Male LowerMiddleIncome Imamia,UC3,Nawabshahdistrict Female LowerMiddleIncome MohammadSalehDeraj Female Katchiabadi

Rural KhairShah Male LowIncome Benazirabad,ObhayoMangsiUC‐Marhabpur

Female LowIncome

HajiJarrarUCMehrapur Male BISP KhairShahSolangiMohalla Female BISP

Total 44 16 12