45 Pages
English

Philippe Andrade Banque de France CREM

-

Gain access to the library to view online
Learn more

Description

Niveau: Supérieur, Doctorat, Bac+8
Inattentive professional forecasters? Philippe Andrade Banque de France & CREM Herve Le Bihan Banque de France October 2010 Abstract We use the ECB Survey of Professional Forecasters to characterize the dynamics of expec- tations at the micro level. We find that forecasters (i) have predictable forecast errors; (ii) disagree; (iii) fail to systematically update their forecasts in the wake of new information and disagree even when updating; (iv) differ in their frequency of updating and forecast perfor- mances. We argue that these micro data facts are qualitatively in line with recent models in which expectations are formed by inattentive agents. However building and estimating an expec- tation model that features two types of inattention, namely sticky information a la Mankiw-Reis and noisy information a la Sims, we cannot quantitatively generate the error and disagreement that are observed in the SPF data. The rejection is mainly due to the fact that professionals' forecasts are too sluggish compared to the ones our inattention model generates. Keywords: Expectations, imperfect information, disagreement, inattention, business cycle ?We thank our discussant Ernesto Pasten as well as Carlos Carvalho, Olivier Coibion, Anil Kashyap, Noburo Kiyotaki, Bartosz Mackowiak, Juan Pablo Nicolini, Giorgio Primiceri, Sergio Rebelo, Jonathan Willis, Alexander Wolman, Michael Woodford, Tao Zha and seminar participants at the Banque de France, ECB, New-York Fed, Philadelphia Fed, San-Francisco Fed, University Paris 1 and the ESEM 2009, AFSE 2010 and SED 2010 conferences for useful comments.

  • lower than

  • aggregate forecasting

  • disagreement among

  • experts disagree

  • forecasting macroeconomic variables

  • inattention

  • professional forecasters


Subjects

Informations

Published by
Reads 54
Language English
InattentiveprofessionalforecastersPhilippeAndradeHerve´LeBihanBanquedeFrance&CREMBanquedeFranceOctober2010AbstractWeusetheECBSurveyofProfessionalForecasterstocharacterizethedynamicsofexpec-tationsatthemicrolevel.Wefindthatforecasters(i)havepredictableforecasterrors;(ii)disagree;(iii)failtosystematicallyupdatetheirforecastsinthewakeofnewinformationanddisagreeevenwhenupdating;(iv)differintheirfrequencyofupdatingandforecastperfor-mances.Wearguethatthesemicrodatafactsarequalitativelyinlinewithrecentmodelsinwhichexpectationsareformedbyinattentiveagents.Howeverbuildingandestimatinganexpec-tationmodelthatfeaturestwotypesofinattention,namelystickyinformationa`laMankiw-Reisandnoisyinformationa`laSims,wecannotquantitativelygeneratetheerroranddisagreementthatareobservedintheSPFdata.Therejectionismainlyduetothefactthatprofessionals’forecastsaretoosluggishcomparedtotheonesourinattentionmodelgenerates.Keywords:Expectations,imperfectinformation,disagreement,inattention,businesscycleWethankourdiscussantErnestoPaste´naswellasCarlosCarvalho,OlivierCoibion,AnilKashyap,NoburoKiyotaki,BartoszMac´kowiak,JuanPabloNicolini,GiorgioPrimiceri,SergioRebelo,JonathanWillis,AlexanderWolman,MichaelWoodford,TaoZhaandseminarparticipantsattheBanquedeFrance,ECB,New-YorkFed,PhiladelphiaFed,San-FranciscoFed,UniversityParis1andtheESEM2009,AFSE2010andSED2010conferencesforusefulcomments.Allremainingerrorsareours.WearealsogratefultoSylvieTarrieuforsuperbresearchassistanceastoClaudiaMarchiniandIevaRubenefortheirhelpwiththeSPFdata.ThispaperdoesnotreflectnecessarilytheviewsoftheBanquedeFrance.e-mails:philippe.andrade@banque-france.fr,herve.lebihan@banque-france.fr1
1IntroductionModelsinwhichimperfectinformationandtheformationofexpectationsactasatransmissionmechanismofeconomicfluctuations—inthespiritofFriedman(1968),Phelps(1968)andLucas(1972)—haverecentlyregainedinterestinthemacroeconomicliterature.1Severalauthors2relateimperfectinformationtotheinattentionofagentstonewinformation,abehaviorthatcanberationalizedbycostlyaccesstoinformationandlimitedprocessingcapacities.Oneappealofthesemodelsistoprovideanalternativechanneltostickypricestoexplainthepersistenteffectsoftransitoryshocks,andinparticularmonetaryshocks,ontheeconomy.Moreover,thisapproachcanparsimoniouslyaccountforpatternsofindividualexpectationsobservedinsurveydatathatareatoddswiththestandardperfectinformationrationalexpectationframework,namelythatforecasterrorsarepredictableandforecastsdifferacrossforecasters.3Inthispaper,weexploitthepaneldimensionofsuchasurveyofforecasts,namelytheECBSurveyofProfessionalForecasters(SPF),toproducemicrofactscharacterizingtheformationofexpectations.Wethenelaborateonthosecharacteristicstoassesswhethermodelsofinattentionaccuratelydescribethebehaviorofforecastersandthusmaycontributetoabetterunderstandingofbusinesscyclefluctuations.Tobeconsistentwiththerecentliteratureweconsidertwotypesofinattentionmodels.Ontheonehand,stickyinformationmodelsdevelopedbyMankiw&Reis(2002)andReis(2006)whereagentsupdatetheirinformationsetinfrequentlybutgetperfectinformationoncetheydo.OntheotherhandnoisyinformationmodelsproposedbyWoodford(2002),Sims(2003)andMac´kowiak&Wiederholt(2009)inwhichagentscontinuouslyupdatetheirinformationbuthaveanimperfectaccesstoitateachperiod.TheECB-SPFisaquarterlypanelstartingin1999surveyingaround90forecastingunitsineitherpublicorprivateinstitutions.Professionalforecastersmaynotberepresentativeoflesssophisti-catedagents,sinceprofessionalsobviouslyallocatesubstantiallymoretime,human,collectingandcomputingresourcestothetaskofforecastingmacroeconomicvariables.Howeverprofessionals’opinionhasbeenshowntospreadtoothertypesofagentsandthereforeinfluenceexpectations1See,amongothers,Woodford(2002),Carroll(2003),Hellwig&Veldkamp(2008)andLorenzoni(2009).Veldkamp(2009)andMankiw&Reis(2010)providesurveys.23Mankiw&Reis(2002),Sims(2003),Reis(2006)andMac´kowiak&Wiederholt(2009).SeeforexampleMankiw,Reis&Wolfers(2003).2
anddecisionsoffirmsandhouseholds(Carroll,2003).Furthermorewemayexpectprofessionalforecasterstobetheagentsinthebestpositiontopayattentiontotherelevantmacroeconomicinformation.Asaresult,theextentofinattentiontonewsamongprofessionalforecasterscanbeseenasalowerboundforotheragents’inattentiontoaggregateconditions.WehighlightfourmaincategoriesofmicrofactsfromtheseSPFdatathatweargueareconsistentwithprofessionalforecastersbehavingasiftheywereinattentive.First,theforecastsofexpertsexhibitpredictableerrorsandsystematicbias.Second,expertsdisagreeastheyreportdifferentpredictionsforthesamevariableatthesameforecastperiod.Moreover,thedisagreementbetweenforecastersevolvesovertime.Third,agentsdonotsystematicallyupdatetheirforecastsevenwhennewinformationisreleased.Furthermore,theforecasterswhoupdatealsodisagreeontheirforecast.Fourth,thefrequencyofupdatingaforecast,theaverageforecasterrorandtherevisionofforecastvaryacrossindividuals.However,thereisnoclearlyinterpretablecorrelationbetweentheseindividualcharacteristics.Toourknowledge,thepresentstudyisthefirsttodocumentinfrequentupdatinginsurveyforecasts.TheoriginalityofourapproachistoexploitthefactthattheEuropeanSPFprovidessequencesofindividualforecastsforthesameevent(variableanddate).Wecanthereforeconstructadirectmicro-dataestimateofthefrequencyofnon-updatingaforecast.Theresultsshowthat,onaverage,eachquarter25%professionalforecastersfailtoupdatetheir1-yearor2-yearforecastsdespitethemacroeconomicenvironmentevolves.Thisfrequencyhasastructuralinterpretation:itcorrespondstothedegreeofinattention,akeyparameterinasticky-informationtypeofmodel.Furthermore,identifyingforecastersthatupdatetheirforecasts,wealsouncoverthattheytoodisagree.Thusthelackofinformationupdatingisnotthesoleresponsiblefordisagreementamongexperts.Evenwhenupdatingtheirforecasts,theydonothaveaccesstothesameinformation.Thisresultisinlinewiththepredictionsofanoisy-informationmodel.Lastly,theindividualdimensionofthedataallowsustoanalyzethecrosssectiondistributionofthedegreeofinattentionandrevealsthatourresultsarenotdrivenbyaspecificgroupofprofessionalforecasters.Wethenturntoaformalempiricalassessmentofinattentionmodels.Moreprecisely,wearguethatthepreviousresultsqualitativelysupportamodelfeaturingtwotypesofinattentionnamelysticky-informationa`laMankiw-Reisandnoisy-informationa`laSims.Wethereforedevelopsuch3
anexpectationmodelandthenuseitalongwiththeSPFdatatocarryoutaminimumdistanceestimation.Wefindthatthisinattentionmodelfailstoquantitativelyreproducetheobservedpersistenceoftheaverageforecastingerrorstogetherwiththerelativelysmalldisagreementbetweenforecasters.Moreover,thesmoothnessobservedintheaverageSPFforecastswouldrequireamuchhigherinattentiondegreethanourmicrodataestimates.SuchahighinattentionwouldinturnleadtomuchmoredisagreementthanobservedintheSPFdata.Therefore,elementsothersthanthemereinattentionincludedinourexpectationmodelareneededtoreconcileboththerelativelylowdisagreementamongprofessionalsandtherelativelyhighpersistenceoftheaggregateforecastingerror.Ourpaperrelatestothevastliterature,mostlyrelyingonUSdata,thatstudiesthebehaviorofsurveyforecastsandcomparesitwiththeimplicationsoftheoreticalexpectationmodels.Numer-ousstudies(seeThomas,1999andPesaran&Weale,2006forsurveys)foundsystematicaggregateforecasterrorsanddisagreementinthesedata,atoddswiththeperfectinformationrationalexpec-tationframework.WeconfirmtheseresultsforarecentsampleperiodandforEuropeanSPFdata.Wealsocomplementtheseresultswithnewempiricalmicroevidenceonindividualexpectations.OurworkisalsorelatedtoMankiwetal.(2003),Branch(2007),Coibion&Gorodnichenko(2008)orPatton&Timmermann(2009)whorelyonthecharacteristicsofsurveyexpectationstoassessinattentionand,moregenerally,imperfectinformationtheories.Mankiwetal.(2003)andBranch(2007)focusonthecross-sectiondistributionofforecaststocalibratethesticky-informationinattentionparameterdiscussedabove.Bycomparison,weunderlinetheimportanceofinvestigat-ingtheconsistencyofthisparametercalibratedvalueswithboththecross-sectionofforecastsandtheaggregateforecasterrors.Furthermore,weimproveontheirapproachbyconsideringamodelwhichcanexplaindisagreementamongforecastersthatupdatetheirinformation.Coibion&Gorodnichenko(2008)lookattheconditionalresponsetovariousstructuralshocksoftheag-gregateerroranddisagreementimpliedbysurveystodisentanglethesticky-informationandthenoisy-informationmodelsofinattention.Theyfindmixsupportinfavorofthetwo,aswedo.Wegoastepfurthersinceweestimatedirectlyamodelthatfeaturesthetwotypesofinattention.Patton&Timmermann(2009)relyontheevolutionofforecastsoverdifferentforecasthorizonstostressthatdifferentperceptionsofinformationratherthandifferentinformationsetsarethemain4