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ID:347028
大小:58.50 KB
页数:10页
时间:2017-07-26
《季度收入模式和盈余管理【外文翻译】》由会员上传分享,免费在线阅读,更多相关内容在应用文档-天天文库。
1、外文文献翻译原文:QuarterlyEarningsPatternsandEarningsManagementEmpiricalevidencesuggeststhatfirmsmanageearningstoavoidreportinglossesorearningsdecreasesortomeetanalysts'expectations.Iffirmsmanageearningstomeetorbeatatargetnumber,adjustmentstoearningsarelikelytobemadewhentheex
2、cessorshortfallfromthetargetbecomesknown.Hence,thetimingofmanipulationislikelytobeacriticaldistinguishingfeaturethatcouldprovideameanstodetectsuchtargetmanagementbehavior.Consistentwiththisview,investmentexpertscautioninvestorstowatchoutforlate-yearsurgesinrevenuesand
3、earnings,whichtheyregardastelltalesignsofearningsmanipulation.Articlesinthebusinesspressdatingbacktothe1990scitecasesoftechnologycompaniesreportingdisproportionateincreasesinrevenuesandearningsinthefourthquarter.Inthispaper,weexploitthetimingconstraintonafirm'sability
4、tomanagetoatargetandexaminewhetherthepatternofquarterlyearningscanprovideanindicationofpotentialearningsmanagement.Ourfocusonpotentialearningsmanagementinthefourthquarterimplicitlysuggeststhatmanagershavegreaterincentivestomanageannualratherthanquarterlyresults.Insupp
5、ortofourassumption,mostaccounting-basedperformancemeasuresusedinbonusandcompensationschemesarebasedonauditedannualearnings.Also,ifcapitalmarketparticipantsperceiveauditedannualearningsasmorecrediblethaninterimearnings,theymayplaceahighervalueonannualearnings,providing
6、managerswithstrongerincentivestomanipulateannualearnings.Thus,althoughmanagersmayhavegreateropportunitiestomanipulateinterimearningsbecauseoftheabsenceofanindependentaudit,theirincentivestomanageearningsininterimquartersmaybeweaker.Thevastliteratureonearningsmanagemen
7、treliesonanaccrualexpectationmodeltoestimateabnormalordiscretionaryaccruals.Empiricalstudiestypicallyidentifyasampleforwhichthedirectionofearningsmanagementispredictedandthentestwhethertheabnormalaccrualsofthesamplesuspectedofearningsmanagementarehigherorlowerthansome
8、benchmark.Theinherentdifficultyinmodelingaccrualsleadstomodelmisspecificationandlowpowertestsresultinginseriousinferenceprob
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