ContentslistsavailableatScienceDirect
The Quarterly Review of Economics and Finance
j o u r n al ho me p a g e :w w w . e l s e v i e r . c o m / l o c a t e / q r e f
Earnings management under different ownership and corporate governance structure: A natural experiment with master limited partnerships
Haiwei Chen
a, Surendranath Jory
b, Thanh Ngo
c,∗aUniversityofAlaskaFairbanks,SchoolofManagement,303TananaLoop,St.201,Fairbanks,AK,99775,UnitedStates
bSchoolofBusiness,UniversityofSouthampton,Southampton,SO171BJ,UnitedKingdom
cEastCarolinaUniversity,DepartmentofFinance,3127BateBuilding,Greenville,NC,27858-4353,UnitedStates
a r t i c l e i n f o
Articlehistory:
Received29November2018 Accepted4May2019 Availableonlinexxx
JELclassification:
G11 G30 Keywords:
Masterlimitedpartnership Corporategovernance Earningsmanagement
a b s t r a c t
Masterlimitedpartnership(MLP)isapubliclytradedpartnershiprunbyageneralpartner(GP)withsole managerialdecision-makingpower,whereaslimitedpartners(LPs)havenoroleintheoperation.Asan alternativeownershipstructuretothetraditionalcorporateownership,MLPsbylawmustpayoutavail- ablecashflowtoGPsandLPs.GPsarecompensatednotbystandardstockoptionsbutbythedistributed cashflow.WefindthattheMLPsengageinmorerealactivitiesmanagementthantheirmatchingcorpo- rationsdo,butnodifferenceindiscretionaryaccrualsmanagement.Sincefirmcharacteristicvariables donothaveamuchmoderatingeffect,thedifferenceingovernancestructuresisnotthekeydriverfor thebehavioraldifference,whichweattributetoamorequickresponsebyGPstochangesinmarket conditions.MLPshavehigherpressuretogenerateaconsistentstreamofearningsandtosmoothcash distributionstotheirunitholders.
©2019PublishedbyElsevierInc.onbehalfofBoardofTrusteesoftheUniversityofIllinois.
1. Introduction
Americancorporationsgrowrapidlyduringthe“GildedAge”
aftertheCivilWarandstarttodominatethedomesticeconomy initiallyandtheworldeconomyaftertheWWII.AlfredChandler (1984)coinstheterm“Americanmanagerialcapitalism”(AMC)to distinguishtheAmericaneconomyfromthosewithlargefamily- controlledfirmsintheUKandGermany.IntheheartofAMCare professionalmanagers,whomustfirststandoutinalargepoolof talentedcandidatesandthengothroughrigoroustraininginbusi- nessprogramsatthetopuniversities.Unfortunately, aseriesof financialscandalsbycorporateexecutives,whichhaveresultedin someinfamousbankruptciesbyseveralwell-knownlargerAmeri- cancorporationsincethe1980s,havetarnishedtheallureofAMC.
Thereareatleasttwo culpritsfor thedecliningoftheAMC.
First,thereistheinherentprincipal-agentconflict.Jensen(1986) hypothesizesthatthemanagement(theagent)hastheincentive tohoardfreecashflow(FCF),ratherthanpayingouttosharehold- ers(theprincipal),andgrowthefirmbeyondtheoptimalsizeat
∗Correspondingauthor.
E-mailaddresses:[email protected](H.Chen),[email protected](S.Jory), [email protected](T.Ngo).
theexpenseoftheshareholders.Asolutiontotheprincipal-agent problemistodistributeFCFtotheshareholdersandbondholders, i.e.,reducingthenumberofextraresourcesavailabletotheman- agement.Fortraditionalcorporations,thereisnolawmandating themanagementtopayoutFCF.Secondly,itiswidelysuspected thattheabuseinrewardinghugestockoptionstothemanagement bycorporateboardssincethe1980sincentivizemisbehaviorsuch asearningsmanipulation.Thevalueofthesestockoptionsdepends onshareprices,whichdependsonearnings.Asaresult,corporate executiveshavetheincentivetomanipulateearningstoboostshare prices.
Althoughthecorporationisthedominantbusinessform,there isanalternativeorganizationalformintheUnitedStates,i.e.,Mas- terLimitedPartnerships(MLPs).MLPsarepubliclytradedlimited partnerships.AnMLPhasonegeneralpartner(GP)andmanylim- itedpartners(LPs).TheGPhasunlimitedliabilityaswellassole decision-makingpower.Incontrast,LPshavelimitedliabilityand noroleindecision-making.Bylaw,MLPshavetopayoutatleast 90%ofthefreecashflow(FCF)toallpartners.Also,aGPreceivesher compensationnotfromanyoptionsbutonlyfromthedistributed FCF. Thesetwo features make MLPs quite special and different fromthetraditionalcorporations.ManylargeMLPsarecompet- ingagainstwell-knowncorporationsintheenergyandrealestate sectors.Mandell(2015)showsanewwaveformationofMLPsafter https://doi.org/10.1016/j.qref.2019.05.005
1062-9769/©2019PublishedbyElsevierInc.onbehalfofBoardofTrusteesoftheUniversityofIllinois.
2004asaresultofamodificationinDelawarealternativeentity lawpermittingthefullwaiveroffiduciarydutybypartnershipsand LLCs.AtanassovandMandell(2018)showthatMLPswithaweak corporategovernancestructuretendtopayouthigherdividends.
Inthis study, weexamine how GPs behavedifferently from theircorporatepeersinpracticingearningsmanagement(EM).EM referstothepracticebytopcorporateexecutiveswhotakeactions tosteerfinancialreportingresultstowardspecifictargets.There aretwo typesofEM.Thefirstisdiscretionaryaccrualsmanage- mentthatinvolvesalteringthetimingandamountsofaccrualsand deferrals.Thesecondtypeisrealactivitiesmanipulationinvolv- ingpurposely-deviatingrealactivitiessuchasproduction,sales, andadministrativeoperation,andR&Dfromthenormallevelto moveearningstowardatargetlevel.Discretionalaccrualsman- agementiseasytoimplementandthusquitecommon.Dechow, Sloan,andSweeney(1996)andDechowandDichev(2002)provide adiscussionontherationale formanagingdiscretionaryaccru- alsandtheearlierevidence.Graham,Harvey,andRajgopal(2005) presentsurveyresultsshowingthatcorporate executivesadmit theirpropensitytoalterrealactivities.Roychowdhury(2006)and Mellado-Cid,Jory,andNgo(2018)provideempiricalevidencefor theeffectsofrealactivitiesmanagementonfirmvaluation.
SomeEMpracticescanbeoutrightfinancialfrauds,butmost arenotnecessarilysobecausethemanagementcanlegallymake adjustmentstoaffectearningsunderthecurrentregulatoryframe- workandaccountingrules.Forexample,undertheUSGenerally AcceptableAccountingPrinciples(GAAP),themanagementhasthe discretionspermissibletoconductdiscretionaryaccrualearnings management.Real earnings managementis alsolegal sincethe managementhasthedecision-makingpowerinadjustingadver- tising,R&D,andotheroperationsovertime.
BecauseMLPspayoutmostoftheavailablecashflowtoshare- holders,themanagementhaslessresourcetosquander.MLPshave toraisefundsatthecapitalmarkettofinancenewprojects;there couldbemoreeffectivemonitoringfromtheinvestorsandana- lysts.IftheGPsoftheMLPsbehavethesameasthemanagementof traditionalcorporations,theeffectivenessinalleviatingtheagency problembythesetwospecialfeatures,i.e.,mandatorydistribution offreecashflowandcompensationbydistributedcashflow,maybe questioned.However,ifGPsbehavedifferentlyfromthemanage- mentoftraditionalcorporations,regulatorsandcorporateboards maybeinterestedinlookingintowhetheramandatorydistribu- tionofFCFandachangeintheexecutivecompensationpractice arewarranted–withoutchangingthebusinessorganizationform.
Thisisthemotivationofourstudy.
Therestofthepaperproceedsasfollows.Section2reviews relatedliteratureand formulatesthehypotheses. Section3dis- cussesthedataandthemethodology.Section4presentsempirical results.Section5discussesthefindingsandconcludes.
2. Reviewofrelatedliteratureandtheformationof hypotheses
Inthissection,wefirstdiscussMLPorganizationstructureand thegovernanceissues.Then,wereviewrelatedpreviousstudies ontherelationbetweencorporategovernanceandEM.Finally,we developseveraltestablehypotheses.
2.1. Masterlimitedpartnershipsorganizationstructure
AGPcanbeaholdingcompanyorapersonappointedbyaspon- soringcompany.ThesponsoringcompanydivestassetstotheMLP andplacingnewassetsorbusinessstreamsintheMLP.AnMLP raisescapitalbyissuingunitstoinvestors,whobecomeunitholders, i.e.,shareholders.Withlimitedliability,LPshavenoroleinman-
Table1
SampleDistribution.
Year MLPs AllNon-MLPs
N % N %
1995 3 0.47 430 5.71
1996 7 1.09 445 5.91
1997 9 1.4 436 5.79
1998 11 1.71 422 5.6
1999 11 1.71 370 4.91
2000 11 1.71 348 4.62
2001 11 1.71 325 4.31
2002 13 2.02 304 4.04
2003 14 2.17 298 3.96
2004 14 2.17 306 4.06
2005 17 2.64 331 4.39
2006 25 3.88 363 4.82
2007 31 4.81 368 4.88
2008 32 4.96 365 4.84
2009 31 4.81 359 4.77
2010 34 5.27 350 4.65
2011 44 6.82 345 4.58
2012 62 9.61 346 4.59
2013 76 11.78 345 4.58
2014 93 14.42 346 4.59
2015 96 14.88 332 4.41
Total 645 100 7534 100
Numberofuniquefirms 99 930
PanelB–ByIndustry
Industry MLPs AllNon-MLPs
N % N %
BituminousCoal&LigniteMining 38 5.89 146 1.94 CrudePetroleum&NaturalGas 121 18.76 3049 40.47
DrillingOil&GasWells 2 0.31 468 6.21
Oil&GasFieldExplorationServices 15 2.33 135 1.79 Oil&GasFieldServices,Nec 5 0.78 346 4.59 Mining&QuarryingofNonmetallicMinerals 9 1.4 229 3.04
IndustrialOrganicChemicals 2 0.31 162 2.15
AgriculturalChemicals 24 3.72 93 1.23
PetroleumRefining 32 4.96 624 8.28
SteelWorks,BlastFurnaces&RollingMills 3 0.47 507 6.73 Trucking&CourierServices(NoAir) 7 1.09 137 1.82
WaterTransportation 8 1.24 342 4.54
DeepSeaForeignTransportationOfFreight 16 2.48 482 6.4
PipeLines(NoNaturalGas) 48 7.44 13 0.17
NaturalGasTransmission 99 15.35 237 3.15
NaturalGasTransmission&Distribution 14 2.17 246 3.27 Wholesale-PetroleumBulkStations&Terminals 68 10.54 82 1.09 Wholesale-Petroleum&PetroleumProducts 45 6.98 139 1.84
Retail-MiscellaneousRetail 89 13.8 97 1.29
agerialdecision-makingbutholdmostoftheunitsissuedbythe partnership(98%inmostcases).Theseunitsaretradedonregu- larstockexchanges.Thus,MLPsarepubliccompaniesandrelease quarterlyandannualreportsaswellasfilingvariousotherreports ofmaterialinformationwiththeSecuritiesExchangeCommission (SEC).MLPsdifferfromtraditionalcorporationsintwoimportant aspects.First,aspass-throughentities,MLPsarenotsubjecttocor- poratetaxation, thus avoidingdouble taxation (i.e.,onceatthe corporateleveland asecondtimeattheindividualshareholder level).Secondly,MLPsmustdistributemostoftheirincometotheir unitholders,whomustpaytaxesontheirdistributedincomefor incometaxpurposes,similartothecaseofpartnersinapartnership.
AsTable1shows,thenumberoflistedMLPsincreasedfrom threein1995toninety-sixin2015.MostMLPsoperateinthenat- uralresourcessectorincludingoil,gasandpetroleumexploration, processing,storage,transportation,pipeline,andrelatedactivities.
ThisisthecasebecauseIRSrulesrequirethatMLPscouldmain- tain theirtax-exemptstatus onlyif theyderiveat least90% of theirincomefromqualifyingsources,whichincluderevenuespre- dominantlyfromnaturalresources,energy,andcommodities.With
recentchangesinlegislationallowingmoreinstitutionalinvestors toownMLPunits(forexample,mutualfunds),andgivenMLPs’
abilitytogeneratehighyieldoninvestmentforinvestorsdueto theirtax-freestatus,weexpectinterestinMLPunitstoincrease.
2.2. Corporategovernanceandearningsmanagement
Evenifitisnotoutrightfrauds,isEMstillharmfultoinvestors?
The answer depends on the degree of sophistication of the investors,corporategovernancestructures,andtheabilityofthe management.Ifthecapitalmarketisefficientandthereiseffective monitoringonthe management, conductingdiscretional accru- alsmanagementisless likelytodistortmarketvaluation.Some researchershaveshownthatthemanagementmayusediscretional accrualsmanagementtosmoothearningsfluctuationortosignal toinvestorsaboutfutureperformance.Subramanyam(1996)and Bowen,Rajgopal,andVenkatachalam(2008)provideevidenceto supportthisso-calledefficientcontractinghypothesisofearnings management.However,ifthecapitalmarketisnotefficientand investorsarenotsophisticated,themanagement canuseEMto entrenchitselfattheexpenseoftheshareholders,e.g.,hidebad news.
Ontheotherhand,ifafirmhasaweakcorporategovernance structure, itsmanagement hasfewerincentives toconduct EM since any repercussion against the management is limited. As reviewedinHealyandWahlen(1999)andFieldsandKeys(2003), previousresearchhasdocumentedalinkbetweencorporategover- nanceandearningsqualityandtheprevalenceofEM.Forexample, Dechowetal.(1996)findthatfirmswithweakcorporategover- nance,e.g.,aboardofdirectorsdominatedbymanagement,are morelikely toengagein EM.Kasanen,Kinnunen,and Niskanen (1996)arguethatfirmsfacedwithathinsecuritymarketandcon- centratedownership have more incentives tomanage earnings upwardstosatisfytheirinvestors’demandsforsmoothdividends.
Lee,Lev,andYeo(2007)findthatfirmswithmoreindependent directors and higher institutional ownership are less likely to engageinearningsmanagement.
Similarly,Cornett,Marcus,andTehranian(2008)findfirmswith higherinstitutionalownershipandhigherpresenceofindependent directorsareassociatedwithalowerlevelofusingdiscretionary accrualsinmanagingearnings.Small,Kwag,andLi(2015)findthat firmswithamoredemocraticcorporategovernancestructureare associatedwithmoreEM.Theirresultsareconsistentwiththecon- jecturethatbettercorporategovernanceexhibitsapressureonthe managementtomeettheearningtargets,whichinturnleadsthe managementtoengageinusingdiscretionaryaccrualsinEM.
Ample empirical evidence also suggests that stock liquidity affectsearningsmanagement.Forinstance,LiandXia(2016)find thatfirmswithlessliquidstocksexhibithigherlevelsofrealearn- ingsmanagement.Theauthorssuggestthatliquiditycurbsearnings managementbymitigatingtheinformationasymmetrybetween agents and theirprincipals and facilitatesgovernance by large institutionalinvestors.BothTeoh,Welch,and Wong(1998)and DuCharme,Malatesta,andSefcik(2001)showthatvaluationsof newequityissuesarepositivelycorrelatedtopre-issueearnings management,suggestingthatexecutivesattempttoopportunisti- callymanipulateearningsbeforeapproachingnewinvestorsinan attempttoraisemorecash.GuthrieandSokolowsky(2010)find thattotalaccrualsincreaseby2%forthosefirmswithlargeout- sideblockholders(holdingatleast5%ofalloutstandingshares) aroundseasonedequityofferings.Incontrast,thosefirmswithout largeoutsideblockholdersdonothaveasignificantincreaseintotal accruals.
2.3. Testablehypotheses
Ontheonehand,theagencyproblemsasdiscussedinJensen andMeckling(1976)maybemoreprevalentinMLPsthanintradi- tionalcorporations.OnecanarguethatGPsofMLPsarenotsubject tothetraditionalcorporategovernancestructure.Anothergover- nanceissueisthatwhiletheLPunitsarepubliclytradedonastock exchange,theGPunitsarenot.TheinabilitytotradetheGPunits makesitverydifficulttodisplaceGPswhenagencyconflictsarise.
Tomakemattersworse,mostpartnershipagreementsthatgovern MLPsstipulatethatanypartyaccumulating20%ormoreowner- shipofanMLP’soutstandingcommonunitsloseitsvotingrights.
Asstatedearlier,mostGPshavedirecttiestoasponsoringcom- panyorentity.Assuch,thesponsormayusetheMLPtomaximize itsinterestsaheadofthoseoftheLPs,e.g.,divestingnonperforming assetstotheMLPandchargingfavorableratesfortheprovisionof managementservices,etc.Thus,thepressureishigherforGPsto actinthebestinterestoftheprincipalsattheexpensesofLPs.As aresult,GPshavemoreincentivestoconductEM.Indeed,areport byMoody’sInvestorsService(2017)statesthatthenatureofthe separationofownershipandcontrolinherenttotheMLPs’corpo- rategovernancestructureleadstheratingagencytosuppressMLPs’
ratingsrelativetopubliccorporationswithcomparablefinancial metrics.Notethatsuchgovernancerisksaredistinctfromandin additiontothecreditandliquidityrisksassociatedwiththeMLP businessmodel.Themaingovernanceriskasperthereportisthat GPsusetheircontroltoextractvaluefromtheMLPtothedetriment oftheircommonunitholders.
On the other hand, there are counter-arguments. First, the sponsoringcompanieshavestrongincentivestoprotecttheirrepu- tationbycloselymonitoringGP’sbehavior.Duetoproximity,such monitoringcanbemoreeffectivethanacorporateboardwhose membersarenotasknowledgeableorhasthepriorworkingrela- tionshipwithGPs.ThelinkthattiessponsoringcompaniesandGPs totheirMLPsisaresemblancetofamily-runfirms.Andersonand Reeb(2003)showthatfoundingfamily tieshelpreduceagency costs.PrencipeandBar-Yosef(2011)findthattheearningsman- agementbehaviorinfamily-controlledbusinessesisaffectedless bythenumberofindependentboardmemberbutmorebyCEO’s tietothefamily.Totheextentthatthesponsoringcompanywould maximizetheMLP’swealth,theincentivestoobtainprivateben- efitsattheexpenseofLPswouldbefewer.Thus,thelong-term tiesbetweensponsoringfirmsandGPsshouldreduceopportunis- ticbehaviorbyGPs.Secondly,asdiscussedinChenandNgo(2018), GPsarecompensatedbydistributedcashflow.Manipulatingcash flowmaybemoredifficultthanmanagingearnings.
ShrievesandGao(2002)andBergstresserandPhilippon(2006) evincethatearningsmanipulationismorepronouncedwhereexec- utive compensationis moreclosely tied tothevalueof shares.
However,sinceGPsreceivebonusesfromthecashflowdistribu- tion,why would aGP eventrytomanage earnings inthefirst place?Thirdly,becauseMLPshavetotapthecapitalmarketmore frequentlythancorporationsdo,theoddsofbeingcaughtinman- aging earningsaremuch higher, whichalsoactsas adeterrent againstactiveearningsmanagementargument.Itneedsempirical evidencetoshedlightonwhetherthereisadifferenceinmanage- mentbehaviorunderthetwoorganizationformats.Therefore,we specifythefollowingtwohypothesizes.
Discretionalaccrualsmanagementhypothesis:thereisnodif- ferencebetweenMLPsandcorporationsinmanagingdiscretional accruals.
Real activitymanagement hypothesis:there is nodifference betweenMLPsandcorporationsinmanagingrealactivities.
3. Sampleselectionandmethodology 3.1. Sampleselection
FollowingChenandNgo(2018),weobtainthelistofmaster- limited partnership firms from the Master LimitedPartnership AssociationandcrosscheckthelistwiththeCenterforResearch inSecurityPrices(CRSP)andCompustatdatabases.Aftermerging theseintoCRSPandCompustatandremovingfirmsinthefinancial industry(SICcodes=6000–6999),weareleftwith99MLPfirms.
Weprovidethenamesofthe99MLPfirmsinAppendix1.Our finalsampleextendsfrom1995−2015.AlthoughApachePetroleum CompanybecamethefirstMLPlistedontheNYSEin1981,thenum- beroflistedMLPsintheenergysectorwasfewerthanthreeinthe early1990s.Assuch,westartthesamplefrom1995inwhichwe havethreeMLPs.Formatchingnon-MLPfirms,weincludeallcor- porationsthatsharethesameSICcodeinthesameyearastheir MLPcounterparts–excludingsharecodesof70and71.
Table1reportsthesampledistributionbyyearinPanelAand byindustry(asclassifiedbythe4-digitSICcode)inPanelB.There isagradualincreaseinthenumberofMLPsovertheyears.Specifi- cally,thenumberofMLPsdoublesin2006.Asexpected,thehighest frequencyofMLPsoccursintheoil,gasandpetroleumindustries (19%ofthesample).MidstreamMLPssuchasthoseengagingin thetransmissionofgasaccountsfor15%ofthesample,andretail- ingMLPsaccountsfor14%,respectively.Thereare645MLP-year observationsand7534non-MLPmatchingfirm-yearobservations with930uniquenon-MLPmatchingfirms.Thereistoomuchrepre- sentationofcrudepetroleumandnaturalgasfirmsinthematching sample,e.g.,40%vs.19%fortheMLPsample.Later,weperform analysesinwhichwematcheachMLPfirmwiththetop5andtop 10non-MLPfirmsclosestinsize.
3.2. Earningsmanagementmeasurements
Discretionaryaccruals(DA),aproxyforaccruals-basedearnings management,ismeasuredbythedifferencebetweentheactualand forecastedlevelsofaccruals.AsshowninEq.(1),wefirstcalculate actualaccruals.
Accrualsi,t=EBXIi,t−CFOi,t (1)
whereEBXIrepresentstheearningsbeforeextraordinaryitemsand discontinuedoperations,andCFOrepresentsthecashflowsfrom operationsforyeartandfirmi.FollowingthemethodsinCohen, Dey,andLys(2008);CohenandZarowin(2010),andZang(2012), wemeasureDAbytheresidualtermfromthefollowingregression inEq.(2).
Accrualsi,t
Assetsi,t−1 =k0+k1 1
Assetsi,t−1+k2 Salesi,t Assetsi,t−1 +k3 PPEi,t
Assetsi,t−1 +ei,t (2)
whereAssetsi,t−1 representstotalassetsinyeart−1.Salesi,tis thechangeinsalesfromtheprecedingyear,andPPEi,tisthegross valueofproperty,plantandequipment.Weestimatetheabove regressioncross-sectionallyforallindustry-yearobservations.
Weconstructthefollowingmeasuresofrealactivitiesmanip- ulation:theabnormallevelofdiscretionaryexpenditure(RDISX);
theabnormallevelofproductioncost(RPROD);andtheabnormal levelofoperatingcashflow(RCFO).CohenandZarowin(2010)sug- gestthatfirmsthatmanagetheirearningsupwardtendtohave unusuallylowdiscretionaryexpenses,andunusuallyhighproduc-
tioncosts,and/orlowcashflowfromoperations.RDISXrepresents theresidualfromthefollowingequation,
DISXi,t
Assetsi,t−1 =k0+k1 1
Assetsi,t−1 +k2 Salesi,t
Assetsi,t−1+ei,t (3) whereDISXi,tisthediscretionaryexpendituresinyeart,i.e.,the sumofresearchanddevelopment(R&D),advertising,andselling, generalandadministrative(SG&A)expenditures.Assetsi,t−1isthe totalassetsinyeart−1andSALESi,t−1isthenetsalesinyeart−1.
Again,weestimatetheaboveregressioncross-sectionallyforall industry-yearobservations.
Toobtainabnormalproductioncosts(RPROD),wefirstestimate thenormallevelofproductioncostsasfollows,
PRODi,t
Assetsi,t−1 =k0+k1
1
Assetsi,t−1 +k2
Salesi,t Assetsi,t−1 +k3
Salesi,t Assetsi,t−1+k4
SALESi,t−1
Assetsi,t−1 +ei,t (4) wherePRODi,tisthesumofthecostofgoodssoldinyeartandthe changeininventoryduringtheyearforfirmi.Weconductacross- sectionalestimationofEq.(4)forallindustry-yearobservations.
Theabnormallevelofproductioncosts(RPROD)ismeasuredasthe estimatedresidualoftheregression.Higherresidualsaresynony- mouswithincreasedinventorylevels,reducedcostofgoodssold, andinflatedearnings.
Becausetheimpactofadjustingrealactivitieswillaffectoper- atingcashflow,Roychowdhury(2006)usestheabnormallevelof operatingcashflowasthethirdproxyforrealearningsmanage- ment.FollowingRoychowdhury(2006),weestimatethefollowing regressionandusetheresidualtomeasuretheabnormallevelof operatingcashflows,i.e.,realearningsmanagement.
CFOi,t
Assetsi,t−1 =0+1
1
Assetsi,t−1 +2
Salesi,t Assetsi,t−1 +3
Salesi,t
Assetsi,t−1 +ei,t (5)
whereCFOi,tistheoperatingcashflowoffirmiinyeart.Asinesti- matingtheothermeasurements,weestimatetheaboveregression cross-sectionallyforallindustry-yearobservations.1
Finally,weusethefollowingmodeltotestthetwoearnings managementhypotheses.ThedependentvariableisanEMmea- surement.ThedependentvariableEMi,tisameasureofearnings managementforfirmiinyeart.Inadditiontothetraditionalearn- ingsmanagementmeasuressuchasRDISX,RPROD,RCFO,andDA, wefollowCohenandZarowin(2010)andZang(2012)bycreating twocompositescores,i.e.RM1,andRM2,whicharemadeupofthe threerealearningsmanagementvariables.First,RM1isthesumof RPRODandRDISX.Second,RM2isthesumofallthreevariables, i.e.RPR,OD,RDISXand,RCFO.Ineachcase,thehigherthevaluesof RM1andRM2,thehigheristhelikelihoodthatthefirmisengaged inrealactivitiesmanipulations.
EMi,t=ˇ0+ˇ1MLPi,t+ˇ2Sizei,t+ˇ3MKTSHAREi,t +ˇ4Debti,t+ˇ5NOAi,t+ˇ6OPERCYCLEi,t+ˇ7ROAi,t +ˇ8MKTBKi,t+ˇ9Liquidityi,t+ˇ10Stockissuei,t
1Weacknowledgethattheinterpretationoftheabnormallevelofcashflowsasa proxyforrealearningsmanagementisnotclear-cut.Forinstance,earningsmanage- mentmeasurestoincreaseabnormalproductioncostscouldleadtoadecreasein cashflows.Conversely,earningsmanagementmeasurestodecreaseabnormallydis- cretionaryexpenditurewouldproducetheoppositeeffect,i.e.theytendtoincrease cashflows.Thus,notallfirmsengaginginrealactivitiesmanipulationswouldbe associatedwithabnormallylowlevelsofcashflowsfromoperations.
Table2
SampleDescriptiveStatistics.
MLPs Non-MLPs MLPsminusNon-MLPs
N Mean Median StdDev N Mean Median StdDev Mean Median t-stats Wilcoxon-stats
DA 643 0.072 0.045 0.229 7,428 0.030 0.028 0.200 0.041 0.017 4.43*** 3.94***
RDISX 527 0.193 0.112 0.278 6,601 0.044 0.034 0.238 0.149 0.078 11.93*** 14.09***
RPROD 594 0.063 −0.001 0.237 7,151 −0.004 −0.015 0.173 0.067 0.014 6.78*** 6.79***
RCFO 645 −0.064 −0.055 0.192 7,458 −0.031 −0.031 0.189 −0.032 −0.024 −4.13*** −4.81***
RM1 501 0.274 0.173 0.415 6,441 0.037 0.015 0.299 0.237 0.157 12.54*** 13.08***
RM2 501 0.208 0.142 0.432 6,377 0.004 −0.004 0.321 0.204 0.146 10.33*** 10.41***
Assets 645 3,821.73 1,380.47 8,039.94 7,532 8,251.77 904.66 29,914.67 −4,430.04 475.81 −9.47*** 5.88***
MKCAP 642 3,009.92 1,152.98 6,066.67 7,507 7,028.22 606.65 27,423.04 −4,018.30 546.34 −10.13*** 8.5***
MKTSHARE 645 0.001 0.000 0.003 7,532 0.003 0.000 0.011 −0.002 0.000 −0.81 0.8
DEBT 645 0.581 0.598 0.229 7,531 0.539 0.545 0.244 0.042 0.053 4.43*** 5.75***
NOA 645 0.959 0.988 0.078 7,531 0.918 0.960 0.120 0.041 0.028 12.31*** 14.44***
OPERCYCLE 592 11.482 16.187 53.447 7,119 −13.411 16.879 2,147.530 24.893 −0.692 0.97 −0.29
ROA 645 0.046 0.041 0.097 7,532 −0.019 0.031 0.255 0.065 0.010 13.49*** 6.72***
MKBK 632 3.352 2.192 5.862 7,492 2.210 1.723 3.034 1.142 0.469 4.84*** 8.37***
LIQUIDITY 645 0.075 0.057 0.064 7,532 0.173 0.083 2.143 −0.098 −0.026 −3.81*** −3.28***
STOCKISSUE 645 0.127 0.043 0.372 7,532 0.071 0.003 0.331 0.056 0.040 3.70*** 5.34***
DEBTISSUE 645 0.290 0.207 0.308 7,532 0.154 0.065 0.252 0.136 0.142 10.91*** 12.98***
BIG8 645 0.848 1.000 0.359 7534 0.817 1.000 0.387 0.031 0.000 2.11** 1.98**
TENURE 645 5.808 4.000 4.799 7,523 7.829 6.000 7.645 −2.021 −2.000 −9.69*** −4.48***
INSTOWN 645 0.241 0.190 0.241 7534 0.299 0.156 0.378 −0.057 0.034 −5.49*** 0.44
NUMANALYST 645 4.442 4.000 3.816 7534 5.042 1.000 7.619 −0.600 3.000 −3.45*** 6.85***
SummarystatisticsareforMLPsandallNon-MLPfirmsinthesameindustryinthesameyear.DAisthediscretionaryaccrual.RDISXistheabnormaldiscretionaryexpenditure.
RPRODistheabnormalproductioncosts.RCFOistheabnormalcashflow.RM1isthesumofRDISXandRPROD.RM2isthesumofRDISX,RPRODandRCFO.Assetsistotal assets.MKCAPismarketcapitalization.MKTSHAREistheratiooffirmsalestototalsalesofallfirmsinthesameindustry.DEBTistheratioofdebt-to-asset.NOAisnet operatingassetsandiscalculatedastotalassetsminuscashandshort-terminvestmentscaledbytotalassets.OPERCYCLEisthedaysreceivableplusthedaysinventoryless thedayspayableatthebeginningoftheyear.ROAisnetincometototalassetsratio.MKBKisthemarket-to-bookratioofequity.LIQUIDITYistheaverageoftheratioof monthlytradingvolumetosharesoutstandingintheyear.STOCKISSUEistheratiooftheamountofsalesofcommonstockandpreferredstockintheyeartothemarket capitalizationofthefirm.DEBISSUEistheratiooftheamountoflong-termdebtissuancetothefirm’sassets.BIG8isthedummyvariableforfirmswithauditorsinthetop 8.TENUREisthenumberofyearstheauditorhasauditedtheclient.INSTOWNisthepercentageofinstitutionalownershipatthebeginningofyear.NUMANALYSTisthe numberofanalystsfollowingthefirm.*,**and***indicatethesignificancelevelsof10%,5%and1%,respectively.
+ˇ11Debtissuei,t+ˇ12Big8i,t+ˇ13Tenurei,t+ˇ14Instowni,t +ˇ15Numanalysti,t+ˇ16SOXi,t+ˇ17ResidRMi,t+ei,t (6)
ThedummyvariableMLPtakesavalueofoneforanMLPand zeroforcorporations,respectively.SOXisalsoadummyvariable toaccountforanyeffectfromthe2002Sarbanes-OxleyAct.Zang (2012)arguesthatmanagersuserealearningsmanagementduring theyear.Byyear-end,shouldtherebeaneedtomanageearnings further,thenmanagersengageindiscretionaryaccrualsmanage- menttomakeupfortheshortfall.Consequently,intheregression ofaccruals-basedearningsmanagement,weincludeameasureof unexpectedrealactivitiesmanipulation(RESIDRM)toproxyfor theextentofrealearningsmanagementusedthroughouttheyear.
Thatis,theunexpectedrealactivitiesmanipulation(RESIDRM),i.e., RESIDRM1andRESIDRM2,aretheestimatedresidualsfromEq.(6) whenRM1andRM2arethedependentvariables,respectively.
WefollowZang(2012)andcontrolforotherfirmcharacteris- ticsthataffectearningsmanagementinEq.(6).ThevariableSize isthelogarithmicvalueoftotalassets.MKTSHAREistheratioof firmsalestototalsalesofallfirmsinthesameindustry.DEBTisthe ratioofdebtovertotalassets.NOAisnetoperatingassets,which iscalculatedastotalassetsminuscashandshort-terminvestment scaledbytotalassets.OPERCYCLEisthedaysofreceivableplusthe daysofinventoryminusthedaysofpayableatthebeginningofthe year.ROAisnetincometototalassetsratio.MKBKisthemarket-to- bookratioofequity.LIQUIDITYistheaverageoftheratioofmonthly tradingvolumetosharesoutstandingintheyear.STOCKISSUEisthe ratiooftheamountofsalesofcommonstockandpreferredstockin theyeartothemarketcapitalizationofthefirm.DEBTISSUEisthe ratiooftheamountoflong-termdebtissuancetothefirm’sassets.
BIG8isadummyvariablecodedasoneforfirmswithatop-8audi- torandzerootherwise.TENUREisthenumberofyearstheauditor hasauditedtheclient.INSTOWNisthepercentageofinstitutional
ownership.NUMANALYSTisthenumberofanalystsfollowingthe firmasreportedbyI/B/E/S.Allthesecontrolvariablesaremeasured attheendoftheprecedingyear.Intheestimation,wealsocontrol foryearfixedeffectsandcalculatethet-statisticsbaseduponthe standarderrorscorrectedforclusteringeffectsbyfirms.
4. Results
4.1. Univariateanalyses
Table 2presents descriptive statistics on theearnings man- agementvariablesandothervariablesusedinthisstudy.PanelA presentscharacteristicsofMLPs,whilePanelBpresentscharacter- isticsofnon-MLPs.NotethatforeachMLPfirm,wefindamatching sampleofnon-MLPfirmsthatsharethesame4-digitSICcodeinthe sameyear.PanelCpresentstestsofdifferencesbetweentheMLP andnon-MLPfirms.Whiletheaverageassetsandmarketcapitaliza- tionsaresignificantlyloweramongMLPsascomparedtonon-MLPs, theirmedianvaluesaresignificantlyhigher,whichsuggestsawide variationinsizeamongtheMLPs.
Importantly,though,anddirectlylinkedtotestingourhypoth- esis,thefindingsinPanelCsuggestthatMLPshavesignificantly higherdiscretionaryaccruals(DA),abnormaldiscretionaryexpen- ditures(RDISX),abnormalproductioncosts(RPROD)andaggregate realactivitiesmanipulation (RM1 andRM2)than theirmatched sampleofnon-MLPfirmshave.Theseunivariatefindingssupport thehypothesisthatMLPsengageinmoreearningsmanagement thannon-MLPsdo.MLPs,however,havesignificantlylowerabnor- maloperatingcashflows(RCFO)thanmatchednon-MLPfirmshave.
SuchalowerRCFOmayindicatethatGPsaresmoothingtheircash flow–relativetotheircorporatecounterpartswhomanageearn- ings.NotethatMLPsarerequiredtopaythevastmajorityoftheir earningsouttotheirpartnersand,therefore,itmakesmoresense forGPstosmoothcashflow.Alternatively,onemayarguethatthe
businessismorestableforMLPsthanforcorporations.However, thisargumentrunsagainstthefactthatbothMLPsmatchingcor- porationsareinthesamebusinesssector.Furthermore,sincethe averagesizeof matchingcorporationsis muchbiggerthan that ofMLPs,itisnotlikelythatMLPsaremoreabletosteerthrough businesscyclesthancorporationscan.Asshownbythevariable MKTSHARE,whichistheratiooffirmsalestototalsalesofallthe firmsinthesameindustry,thereisnodifferenceinthemeasure- mentofmarketpowerbetweenMLPsandmatchingcorporations.
Thus,itisnotlikelythatMLPsusetheirmarketpowerinweath- eringbusinessfluctuationsbetterthanthematchingcorporations do.Inaddition,asindicatedbythevariableOPERCYCLE,whichis thedays’receivableplusthedays’inventorylessthedays’payable, thereisnosignificantdifferenceinworkingcapitalmanagement efficiencybetweenMLPsandthenon-MLPmatchingfirmsfrom thesameindustry.
PanelCofTable2alsoshows thatMLPshavea significantly higherdebt-to-assetsratio.Althoughtheycannotdeductinterest expensesfortaxpurpose,MLPsstilluseconsiderablymoredebt thanthematchingcorporationsdo.Weconjecturethatthisisdue totwofactors.First,debtisstillcheaperthanequityevenonthe before-taxbasis.Second,GPsarequitegoodatmanagingthefinan- cialrisksincetheywithunlimitedliabilityareresponsibleforany debtdefault.MLPsalsohavehighernetoperatingassetsthanthe matchingcorporationsdo,indicatingthatMLPshavetousecapital morewiselysincetheyareconstrainedwithlimitedresourcesafter payingoutdistributedcashflow.Notsurprisingly,boththemean andmedianvaluesofSTOCKISSUEandDEBTISSUEaresignificantly higherforMLPsthannon-MLPs.Asdiscussedearlier,MLPshave agreaterneedtoaccessthecapitalmarketsmorefrequentlythan non-MLPs.MLPsenjoyahigherreturnonassets.Also,byaffording MLPsahighermarket-to-bookratio,investorslikeMLPsmore.
Ontheotherhand,MLPshavelowerliquiditythanthematching corporationsinthesameindustrydo,asindicatedbythevariable LIQUIDITY.Althoughthenumberofthetop-8auditorsusedbyMLPs isbiggerthanthatusedbythenon-MLPfirms,theaveragetenure oftheauditorissignificantlyloweramongMLPfirms.Similarly, thepercentageoffirmsharesheldbyinstitutionalownersislower amongMLPfirmscomparedtothecasewithnon-MLPfirms(24.1%
vs.29.9%).TheaveragenumberofanalystscoveringeachMLPfirm issignificantlylowerthanthatofnon-MLPfirms(4.42versus5);
however,themediannumberofanalystscoveringeachMLPfirm ishigherthanthatofnon-MLPfirms(4versus1).Thehigherstan- darddeviationofthenumberofanalystsamongnon-MLPfirmsas comparedtoMLPssuggestsawidedispersionofanalystcoverage amongnon-MLPfirms.
4.2. EarningsmanagementbetweenMLPsvs.non-MLPfirms– wholesample
ThepreliminaryresultsinTable2suggestthatMLPfirmsengage inmorerealearningsmanagementthannon-MLPfirmsinthesame industry.However,giventhatmanyofMLPfirms’characteristics aredifferentfromthoseofnon-MLPmatchingfirms,thedifferences intherealearningsmanagementmightbeattributabletootherfirm characteristics.InTable3,weperformtheunivariatecomparison ofearningsmanagementmeasuresbetweenMLPfirmsandnon- MLPfirmsmatchedonalternativefirmcharacteristics.Wematch eachMLPfirmwithanon-MLPfirminthesameindustrywiththe closest(1)assets(inPanelA),(2)marketcapitalization(inPanel B),(3)market-to-bookratio(inPanelC),(4)returnonasset(in PanelD),(5)debtratio(inPanelE)and(6)salesgrowth(inPanel F).Thesixfirmcharacteristicsareobtainedfortheprecedingyear.
Regardlessofthematchingcriteria,therealearningsmanagement (RM1andRM2)areconsistentlyandstatisticallyhigheramongMLP firms.
InTable4,wereporttheresultsfromcross-sectionalanalyses oftheearningsmanagementmeasures.AsshowninTable4,the coefficientsfortheMLPvariableissignificantlypositiveinModels 1and2.Therefore,MLPsengageinsignificantlymorerealactivities adjustmentsindiscretionaryexpensesandproductioncoststhan non-MLPmatchingfirmsdo.However,thecoefficientfortheMLP dummyvariableinModel3isinsignificant.Thisresultisdiffer- entfromtheunivariateresultinTable2butisconsistentwiththe resultinTable3.Therefore,aftercontrollingforcontributingfactors suchasoperatingefficiency,institutionalownership,andfinancial leverage,MLPs arenodifferentfromthematching corporations regardingsmoothingoperatingcashflow.
Nevertheless,resultsfromModels4and5indicatethatMLPs domake moreadjustmentin responsetounexpectedshocksin demandandsupplyasthecoefficientsfortheMLPdummyvari- ablearehighlysignificantinbothmodels.ResultsfromModels6, 7and8showthatthecoefficientsontheMLPvariablearestatisti- callyinsignificant,suggestingthatMLPfirmsdonotengageinmore accruals-basedearningsmanagementthanthenon-MLPfirmsdo.
InModels7and8,thecoefficientsforbothmeasurementsofthe likelihoodofengaginginrealactivitiesmanagementaresignifi- cantlypositive,indicatingcoordinatedearningsmanagement,i.e., thoseengaginginrealactivitiesmanagementalsoconductdiscre- tionalaccruals-basedearningsmanagement.2
IntherealactivitiesmanagementregressionsinModels1–5, thecoefficientonfirm sizevariableisinsignificant,and neither is that for the variable of market-to-book ratio. As shown in Roychowdhury(2006),sizeisnegativelyrelatedtotheabnormal CFObutpositivelyrelatedtobothabnormaldiscretionaryexpenses andabnormalproductioncosts.However,thevariableMKTSHARE hasasignificantlypositivecoefficientinModels2–5,indicatinga morequicklyresponsefromthosefirmswithalargermarketshare.
Theothercontrolvariableswithasignificantcoefficientarefinan- cialleverage,OPERCYCLE,ROA,numberofanalystscoveringafirm, andthedummyvariableSOX.
In thediscretionaryaccrualsregressions in Models6, 7 and 8,thecoefficientsforseveralcontrolvariableshavetheexpected signs.For example, firmsize hada significantly positive coeffi- cient,whichisconsistentwiththatinHaw,Hu,Hwang,andWu (2004).Similarly,netoperatingassetsratiohasasignificantlyneg- ativecoefficient,indicatingalowerpropensityforthemanagersto engageinearningsmanagementusingdiscretionalaccruals.How- ever,several controlvariables arenot significant,e.g., financial leverage,market-to-bookratio,andinstitutionalownership.Previ- ousstudieshaveproducedcontrastingresults.Forexample,while Chung,Firth,and Kim(2002)documenta significantlynegative relationbetweendiscretionaryaccrualsmanagementandfinancial leverage,Hawetal.(2004)findasignificantlypositiverelation.Our resultontheprofitabilityvariable(ROA)alsocontrastswiththatin Hawetal.(2004).Specifically,wefindasignificantlynegativecoef- ficient,whichcontrastswiththepositivecoefficientasdocumented inHawetal.(2004).
TheownershipstructureofMLPswarrantsacarefuldiscussion ontheinterpretationoftheresultsinTables2and4.Onemaynot attributetheseresultstoalackofinternalcorporategovernanceof MLPs.GPsneedtomanagerealactivitiesinresponsetochangesin marketconditionsmorethantheircorporatecounterpartsdofor thefollowingreasons.First,MLPsneedtoapproachinvestorsfor cashmoreoftenthancorporationsdo,andtheirabilitytoattract newfundsdirectlydependsontheirabilitytogeneratecashflow.
2Theresultsremainqualitativelyunchangedwhenwerepeattheanalysesinthe twosubsamplesthatonlycontainthetop5andtop10non-MLPfirmsclosestin size,respectively.Forthesakeofbrevity,wedonotreporttheminthepaperbut areavailableuponrequest.
Table3
UnivariateComparisonofEarningsManagementbetweenMLPsandNon-MLPFirms–AlternativeMatchingCriteria.
Variables MLPs Non-MLPs Difference t-stats Wilcoxon-stats
PanelA.MLPsvs.Non-MLPsClosestinAssets
RDISX 0.198 0.154 0.044 2.62*** 3.45***
RPROD 0.065 0.044 0.021 1.46 1.47
RCFO −0.063 −0.064 0.000 0.03 0.34
RM1 0.282 0.209 0.074 2.7*** 3.01***
RM2 0.218 0.146 0.072 2.54** 2.61***
DA 0.067 0.010 0.057 4.61*** 5.21***
PanelB.MLPsvs.Non-MLPsClosestinMarketCapitalization
RDISX 0.197 0.163 0.035 1.98** 2.68***
RPROD 0.063 0.020 0.043 3.3*** 2.35**
RCFO −0.065 −0.071 0.006 0.59 1.02
RM1 0.279 0.188 0.091 3.44*** 3.43***
RM2 0.214 0.112 0.102 3.75*** 3.48***
DA 0.066 0.032 0.035 2.78*** 3.29***
PanelC.MLPsvs.NonMLPsClosestinMarket-bookRatio
RDISX 0.200 0.150 0.050 2.83*** 2.43**
RPROD 0.065 0.010 0.054 3.81*** 3.33***
RCFO −0.065 −0.070 0.005 0.49 0.66
RM1 0.284 0.163 0.121 4.39*** 3.92***
RM2 0.218 0.091 0.127 4.42*** 3.95***
DA 0.066 0.025 0.040 3.02*** 2.61***
PanelD.MLPsvs.NonMLPsClosestinROA
RDISX 0.197 0.153 0.043 2.49** 3.16***
RPROD 0.065 0.007 0.058 4.22*** 4.41***
RCFO −0.063 −0.079 0.016 1.47 1.62
RM1 0.281 0.163 0.118 4.46*** 4.63***
RM2 0.216 0.076 0.141 5.14*** 4.75***
DA 0.068 0.028 0.040 3.18*** 3.47***
PanelE.MLPsvs.NonMLPsClosestinDebtRatio
RDISX 0.198 0.141 0.058 3.62*** 3.59***
RPROD 0.065 0.034 0.031 2.28** 1.87*
RCFO −0.063 −0.070 0.007 0.61 0.62
RM1 0.283 0.185 0.098 3.93*** 3.47***
RM2 0.218 0.120 0.098 3.75*** 3.1***
DA 0.067 0.011 0.056 4.05*** 3.81***
PanelF.MLPsvs.NonMLPsClosestinSalesGrowth
RDISX 0.203 0.128 0.075 3.85*** 4.46***
RPROD 0.071 −0.012 0.083 5.18*** 4.33***
RCFO −0.060 −0.069 0.009 0.79 1.07
RM1 0.294 0.118 0.177 5.65*** 4.78***
RM2 0.234 0.045 0.189 5.95*** 5.01***
DA 0.070 0.018 0.052 3.83*** 3.58***
ThistableprovidestheresultsfromthecomparisonofearningsmanagementmeasurementsbetweenMLPsandtheirmatchingNon-MLPfirmsinthesameindustrywith theclosestinassets(PanelA),marketcapitalization(PanelB),market-to-bookratioPanelC),returnonasset(PanelD),debtratio(PanelE),andsalesgrowth(PanelF).The matchingcriteriaareobtainedfortheprecedingyear.*,**and***indicatethesignificancelevelsof10%,5%and1%,respectively.
Secondly,theMLPbusinessmodelisstructuredaroundgenerat- inganddistributingcashconsistently(onaquarterlybasis),andits primaryobjectiveistomaintainorincreasecashdistributionsto itscommonunitholders.MLPs’cashdistributionstotheirinvestors tendtostayrelativelystableovertimecausingthemtotradesome- whatlikebonds.ThisalsomakesMLPshighlyvulnerabletochanges ininterestrates.Lately,whileinterestrateshavebeenstable,ithas notalwaysbeenthecase.Indeed,theinterestratesthatcorpora- tions(includingMLPs)payarehigherandmorevolatilethanthe ratesonTreasurysecurities.Increasesininterestratesadversely affectMLPsasinvestorsmovefundstothebondmarket.ManyMLPs operateinslow-growingindustries,suchaspipelines,whichoffer dimprospectsforunitpriceappreciation.Thus,savingsthrough restructuringactivitieswouldserve tomitigateadverseinterest ratemovements.Thirdly,thebulkof MLPsresideintheenergy sector,volatilityinenergyprices(forinstance,oilprices)would hinderMLPs’abilitytopayastable,growingdividendconsistently overtime.Realearningsmanagementwouldassistinsmoothing out theeffects of pricevolatilities on MLPs’ earnings and cash distributionsoverbusinesscycles.Forinstance,GPsmayelectto decreasediscretionaryexpensestoconservecashinordertosur- viveadownturn.Similarly,MLPsmayalsoneedtoconvertsome oftheirdebtintoequitytoconservecash,whichrequireschanges
madetotheMLP’soperationsaswellaspostponingdiscretionary expenses.
Kasanenetal.(1996)arguethatfirmsfacedwithathinsecurity marketandconcentratedownershipareincentivizedtomanage earningsupwardstosatisfytheirinvestors’demandsforsmooth dividends.ThiswouldbeparticularlytrueofMLPs,whoseinvestors treattheMLPunitsasfixed-incomesecurities.Theauthorsfind that dividend-based earnings significantly explain variations in reportedearnings.MLPsprovide12-monthforecastsoftheircash distributionsand,similartotheearningsforecastsofpubliccor- porations,theMLPforecastsimposepressureontheirGPstofind waystogenerateincome andcashtopaytheplannedcash dis- tributions.Otherwise,failuretomaintaininvestors’expectations ofthecashdistributionswouldforcethetradingpriceoftheLP unitsdownward.Thispressuretomanageearningsandcashcre- ativelyis furtherexacerbated ifwe considerthat MLPs usually distributecashwithindaysfollowingthereportingperiod.Finally, MLPsoperatingintheenergysectortendtobethetargetsofenvi- ronmentalactivists,whichresultsinsignificantincrementalcosts –forinstance,environmentalandlegalcosts–aswellasthose relatedtocorporatesocialresponsibility(CSR)activities.Tomake matters worse and in response tothe activists’ demands, gov- ernmentsrequiresignificantlymorediligencefromMLPsbefore
