IPO Failure Risk by Industry, AuditorIndustry Specialization, and Audit Fees

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Authors Todd, Lauren Louise

Publisher The University of Arizona.

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Link to Item http://hdl.handle.net/10150/144995

1

IPOFailureRiskbyIndustry,AuditorIndustrySpecialization,andAuditFees

LaurenToddUniversityofArizona

ABSTRACT:This paper expands the extant literature on IPO failure risk in researchingwhethersignificantdifferencesexistbetweenindustriesintheriskoffailurewithin5yearsofanIPO. Ibasemytestof IPOfailureriskonamodeldevelopedbyDemersandJoos intheirpapertitled“IPOFailureRisk”(2007).IfurtherexplorewhichoftheBig4auditfirmsspecialize in those industries foundtoberiskyaccording to theDemers/Joosmodel,andlastly determinewhether firms that arenot specialists in a risky industry charge higheraudit fees to audit clients in that given industry. In providing industry‐specific IPO riskanalysis, this paper broadens the audit profession’s knowledge base for accuratelyassessingauditriskandforappropriatelysettingauditfees.Keywords:IPOfailurerisk,auditorspecialization,auditfees,industryclassificationDataAvailability:Thedataareavailablefrompublicsourcesidentifiedinthepaper.

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I.Introduction

IPO failure risk, auditor specialization, and audit fees are all highly talked‐abouttopics in the realm of accounting research today. The assessment of IPO companies isimportanttomanydifferentstakeholdergroups,particularlysincethefailurerateofIPOshascontinuouslyincreasedovertime.1Asmoreandmorefirmsenterthepublicmarket,itis vital for auditors to remain knowledgeable of the risk quality of their clients toadequatelyprepareforengagements,makestrategicbusinessdecisions,andtoaccuratelyestimatehowmuchinauditfeestochargespecificclients.

ElizabethDemersandPhilipJoosexploresomeofthefactorsthatcontributetoIPOfailure in their paper titled “IPO Failure Risk” (2007). They develop an IPO failureprediction model using various accounting and other IPO‐related variables, finding thatsignificantdifferences canbeobservedbetweenhigh tech andnontech firm subsamples.Thissuggeststhatriskoffailureisaffectedbytheindustryofthespecificfirm,whetheritisclassifiedashightechornontech.IextendthisstudybyobservingthetrendsofIPOfailurerisk within 5 years of going public for individual industries using a unique industryclassification. I predict and show statistically significant differences in IPO failure riskbetweenparticularindustries.

Furthermore, I explore auditor concentration over the 1990‐2010 period toexaminehowtheBig4auditfirmsappeartomanagetheirIPO‐clientportfoliosinrelationto risk of failure. Assuming that auditors are in business to make money, it seemsreasonable that the Big 4 would strategically fill their client portfolios in a way thatmitigatesrisk,orthattheywouldcontrolforsuchriskbyincludingariskpremiumintheauditfeeschargedtoriskyclients.2Thus,auditorsmaybeobservedtoactasspecialistsinthoseindustriesfoundtoberisky,mitigatingriskthroughexpertise,orauditorsmaytakeon risky clients in industries in which they are not specialists, controlling for risk bycharginghigherfees.

ThepurposeofthispaperistonotonlyexpandtheextantliteratureonIPOfailurerisk based on industry specific analyses, but to apply the results to the area of auditorspecializationtrends. Myresearchisbasedprimarilyonthefoundationsofothers’work,but this paper does in fact document new and interesting trends for today’s accountingaudience.Priorliteratureshowsthatauditors’knowledgeoftheirclient’sindustryenablesthem to better assess audit risk.3 Therefore, a better understanding of industry‐specificriskassociatedwithIPOclientswillnodoubtbenefittheauditingprofession.

Ihavethreebasicresearchquestionsthatareansweredinthecourseofthispaper.InexpandingtheIPOfailureriskmodeldevelopedbyDemersandJoos,Icometomyfirstresearch question: (1)Are there significant differences between industries in the risk offailurewithin5yearsofanIPO?Inextexaminehowsuchindustryriskisreflectedinbothauditor specializationandaudit fees, leading tomysecondand third researchquestions:(2)WhichBig4auditfirmsarespecialistsintheriskyindustriesdeterminedfromtestingRQ1? and (3) For those firms that arenot specialists in a risky industry, do they chargehigherauditfeestoauditclientsinthatgivenindustry?

Based on the Demers and Joos paper, as well as other extant literature on thesubjectof IPOfailurerisk, I formthefollowingthreehypotheses inresponsetomythreeresearchquestions:

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H1:SignificantdifferenceswillbeobservablebetweenspecificindustrysubsamplesintheriskoffailurewithinfiveyearsofanIPOwithinthe1990‐2010timeperiod.H2a:Big4auditorspecializationwillbemorecommoninindustrieswhereriskoffailurewithinfiveyearofanIPOishighestduringthe1990‐2010timeperiod.H2b: For those Big 4 firms who take on clients in risky industries where they are notspecialists,higherauditfeeswillbecharged,asobservedpost2002to2010.

The balance of this paper is as follows: Section II provides a discussion of thesample selectionanddescriptive statistics, Section III details the results from testingmythreehypotheses,andSectionIVincludesmyconclusionandfinalremarks.II.SampleSelection,DescriptiveStatistics The sample of firms used is from the Securities Data Corp. (SDC) New Issuesdatabasewith a selection of all U.S. IPOs from January 1990‐December 2010. I excluderights issues, unit offerings, spin‐offs, Real Estate Investment Trusts (REITs), AmericanDepository Receipts (ADRs), and financial institutions. This results in a total sample of1,962firms. Usingabinarylogitregressionwherefailure=1,itisfoundthat602firms(30.68%)were delisted within five years of going public during the 1990‐2010 time period, (seeTable1). It isrelevanttonotethatdelisting isusedhereasaproxyfor failure; it is thuspossible that a firm that delisted within five years of an IPO simply returned to beingprivately‐heldratherthandelistingasaresultofbankruptcy.

I classify the total of 1,962 firms observed into 15 subsamples based onmy ownunique industry classification scheme that isbased somewhatonFamaandFrench’s17‐industryportfolio.4Myclassificationisgenerallythesame,butIforcedallindustrieswiththesamefirst2‐digitsofitsSICcodetobeinthesameindustrysubsample(seeAppendix).Table 2 lists each of these 15 industry subsamples by name and with correspondingstatisticssuchasnumberofU.S.IPOsfrom1990‐2010withaBig4auditorinthatindustry,failurefrequency,andoverallfailurerate.

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Figure 1 belowdepicts the failure rate for each of the 15 industry subsamples ingraphicalform:

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ItalreadyappearsfromthedescriptivestatisticsdisplayedinTable2andFigure1that there are significant differences between industries in the risk of failurewithin fiveyearsofanIPO.Communications,HealthServices,andRealEstatehavethehighestratesoffailure with 58%, 50%, and 39.29%, respectively, whereas Utilities, Chemicals, andTransportation have the lowest rates of failure with 15%, 20.45%, and 21.88%,respectively.Thismatchesgeneralizedexpectationssincethesethreehigh‐riskindustriestendtobemorevolatileinrelationtomacroeconomicconditions,whereasthesethreelow‐riskindustriesareusuallylessvolatile,astheyrequiremuchmoregovernmentregulation.III.Results IntestingH1,IuseasimplifiedversionoftheDemersandJoosmodelforpredictingIPO failure risk. The five controls used for themodel include “size” as a control for therelative firmsize,“cm_rank”tocontrol forunderwriterqualityusingtheCarter‐Manasterunderwriter reputation ranking, “vcdummy”asan indicatorvariable setequal to1 if thefirmisventurecapitalist‐backedatthetimeoftheIPO,“firstdayret”representingfirstdayinitialreturns,calculatedasclosingpriceontheIPOdatelesstheofferpriceasapercentofthe offer price, and lastly “offer_price” as the IPO offer price adjusted according to theConsumerPriceIndexonthatdate. Tables3and4displaytheresultsofrunningtheregressionfortestingH1.Table3revealsanoverallsignificanceinriskofIPOfailurebetweenspecificindustries,asshowninthe satisfied convergence criterion for themodel and the highly significant results fromtesting the null hypothesis. These results show that H1 is true; there are significantdifferencesbetweenparticularindustriesintheriskoffailurewithinfiveyearsofanIPO.

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Table4summarizes theresultsof testingH1by industry, revealingwhichspecificindustriesholdsignificantresultsintheirriskofIPOfailure.Namely,industries2,4,11,12,13,and15hadsignificantlydifferentfailurerates.Theseindustriesare,inthesameorder,“Mining, Minerals, Oil, Petroleum,” “Tobacco, Chemicals,” “Real Estate, Hotels, Camps,Lodging,” “Communications,” “Health Services,” and “AllOther.” Fourof these industrieswithsignificantlydifferent failureriskalsorepresentthe four industrieswiththehighestrates of failurewithin five years of IPO: Communications (58%),Health Services (50%),RealEstate(39.29%),andMining(34.78%).

Table4

As seen in Tables 3 and 4, these results show that there are in fact significant

differences between specific industries in the risk of failurewithin five years of an IPO,makingH1true.Themodeloverallhassignificantresults,andmorespecifically,Industry2(Mining),11(RealEstate),12(Communications),and13(HealthSciences)areallfoundtohavesignificantlyhighfailurerates.IntestingH2a,IexaminetheauditorconcentrationbyBig4firmthroughoutthe1990‐2010timeperiodtoseeifauditorsspecializeinthesefoursignificantlyhigh‐risk industries. Tables5 and6 summarizemy testingofH2a. Table6showsthe“specialist”ineachindustryasdeterminedbywhichauditfirmhasthegreatestpercentageofIPOclientsinthatgivenindustrysubsample.

Iseparatedthe1,962firmsintothreeordersbasedonfailureratetobetteranalyzethe results for testing H2a. Order 1 represents low risk (17.39% failure rate), order 2medium risk (33.05% failure rate), and order 3 high risk (43.32% failure rate). Thestatistics for each of these orders is shown in Table 5, revealing significant results fororders1and3.Thereisasignificantcorrelationbetweenindustryfailureriskandauditor

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FortheentiremarketofIPOfirmsauditedbytheBig4throughoutthe1990‐2010timeperiod, itappearsthatPwCandErnst&Youngleadwith32.72%and29.71%ofthemarket, respectively. The spread in market share between the four firms ranges fromindustryto industrywithamaximumspreadof40.38%inthe“HealthServices” industrywhereErnst&Youngauditedover50%ofallsuchU.S.IPOsfrom1990‐2010.Thiswasoneof the industrieswhere tests forH1 revealed significant results in itshigh riskof failurewithinfiveyearsofanIPO. Ernst&Youngappearstohavechosenastrategyof industryspecializationtomitigateriskthroughexpertiseinthehigh‐risk“HealthServices”industry.This is just one example, then, of the significant correlation between failure risk andauditorspecializationinthehigh‐riskindustryorder.

The other high‐risk industries besides “Health Services”, as determined in testing

H1,haveeithersmallormoderatespreadsinTable4. Communications, forexample,hasone of the lowest spreads of 7%, but this is most likely due to the fact that theCommunications industry has been highly regulated until fairly recently, leaving theindustrywithlessriskfactorsthanmightexistotherwise.Theremainingtwo,significantlyhigh‐risk industrieshave similarly small spreads: “Mining,Minerals,Oil,Petroleum”with10.87%and“RealEstate,Hotels,Camps,Lodging”with17.86%. Overall,theresultsrevealasignificantcorrelationbetweenfailureriskandauditorspecializationforboththelowandhigh‐riskordersubsamples.Auditorsthendoappeartorespond to low and high‐risk industry clients in a systematic way to account for riskthroughspecialization.AsseenwithErnst&Younginthe“HealthServices”industry,itisclear thatBig4auditorsdopracticespecialization inhigh‐risk industries tomitigateriskthroughexpertise.

Furthermore,itisinterestingtonotethatErnst&Youngholdsasubstantialshareofthe market for the Health Services, Utilities, Construction, and Chemicals industries,whereas PwC holds the lion’s share in the Food, Machinery, Real Estate, and BusinessServices industries. Neither Deloitte nor KPMG specialize in any of the IPO industry

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subsamplesastakenfromthe1990‐2010timeperiod.Itmaythenbepostulatedthatthesetwo firmscontrol for IPOfailurerisk incharginghigheraudit feesrather thanmitigatingriskthroughexpertiselikeErnst&YoungandPwCappeartodo. H2b tests thevalidityof thispostulationbyestimating thesignificanceofamodelwhere audit fees serves as the dependent variable and firm size, failure estimate, andindustryspecializationserveastheindependentvariables.AregressionofthismodelgavetheresultsassummarizedinTable7.

Table 7 shows insignificant results for both the failure estimate and industryspecialization variables, indicating that there is no significant correlation between theseindependentvariablesandauditfees. Moreover,auditorswhoarenotspecialistsinhigh‐risk industries apparently do not charge a risk premiumwith significant consistency torevealacorrelationbetweenauditfeesandauditorspecialization.Thisresultcontradictsmyexpectations,makingH2bfalse.

Apparentlyauditfeesarenotsignificantlydependentonrelativeauditrisknorarethey a function of auditor specialization. Basic reasoning and common‐knowledge riskmanagement strategy dictates that audit fees should depend on risk and auditorspecialization. Itwould not bewise to take on a risky client unless the auditor (1) is aspecialist and can mitigate risk through its expertise, or (2) charges a risk premium inadditiontotheregularauditfees.H2b’stestresultsarethussurprisinginnature.

Lastly, theseresults indicateaneedforchange intheauditprofession. GiventhattheBig4arecapableofdetermining industryriskandare inbusiness tomakemoney, itwouldonlymakesensethattheyaltertheirbusinessstrategytoonewhereauditfeesare

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dependentonindustryfailureriskandauditorspecialization.Otherwise,thoseauditfirmsthatarenotspecialistsinagivenhigh‐riskindustryarenotpracticingeffectivecontrolsinmitigatingriskthroughchargingariskpremiuminadditiontoregularauditfees.IV.SummaryandConclusion While the Demers and Joos paper examines how IPO failure risk differs betweenhightechandnontechindustrysubsamples,verylittlehasbeendocumentedintheextantliteratureonhowthisriskdiffersbetweenspecificindustries.Iuseaunique,15‐industryclassification to assess the relative riskof failurewithin five years of an IPO. I find thatsignificantdifferencesdoexistbetweenindustrysubsamples,makingH1true. Industries2,4,11,12,13,and15allhavesignificantdifferencesintheirfailurerates.

FurtherexaminationintestingH2arevealsthatauditorsdopracticespecializationinparticular industrysubsamples. Asignificantcorrelation is foundbetween failureriskandauditorspecialization forboth the lowandhigh‐riskorders.H2a is thus found tobetrue.Ernst&Youngappearstousethespecializationtechniqueofriskmitigationinhigh‐risk industries, namely in “Health Services.” The results show that the Big 4 do in factsystematicallymatch‐upwithindustriesbasedontheirriskquality.

Lastly, I find that for those firms that are not industry specialists, they do notnecessarily charge a risk premium in addition to normal audit fees. No significantcorrelationisfoundbetweenauditfees,industryspecialization,andfailurerisk,causingmyH2b tobe false. Thisresult is surprisingandcounterintuitive; thus, futureresearchmayserve a purpose in better understanding the relationship between audit fees, industry‐specificrisk,andauditorspecialization.

1FamaandFrench, 2004: theprobability that anewly listed firmwill surviveduring the first 10 years fellfrom 61.0% in the 1973 subsample to just 37.0% in the 1991 subsample; seasoned firms also showed adecreaseinsurvivalratefrom60.6%to46.9%

2Venkataraman,Weber,andWillenborg,2008: their findingssupport thenotionthataudit feesreflectbotheffortandtimespentontheengagement,aswellasapremiumtocoverlitigationrisk3HoganandJeter,1998:evidencesuggeststhatinvestinginspecializationyieldpositivereturnsasauditfirmscontinuetoseekspecializationinbothregulatedandnon‐regulatedindustries4SeeFamaandFrench’s17‐industryportfolio:http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/

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V.Appendix

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VI.ReferencesDanos,Paul,andJohnW.Eichenseher.“TheAnalysisofIndustry‐SpecificAuditor

Concentration:TowardsanExplanatoryModel.”TheAccountingReview3(1981):479‐492.

Demers,Elizabeth,andPhilipJoos.“IPOFailureRisk.”JournalofAccountingResearch2(2007):333‐371.

Hogan,ChrisE.,andDebraC.Jeter.“IndustrySpecializationbyAuditors.”1998.“IndustryRiskRatings.”IBISWorld:WhereKnowledgeisPower.

<http://www.ibisworld.com.au/riskrating/home.aspx>.December10,2010.Low,Kin‐Yew.“TheEffectsofIndustrySpecializationonAuditRiskAssessmentsandAudit‐

PlanningDecisions.”TheAccountingReview1(2004):201‐219.Wright,Arnold,andSallyWright.“TheEffectofIndustryExperienceonHypothesis

GenerationandAuditPlanningDecisions.”