THEFLATTENINGFIRM: EVIDENCEFROMPANELDATAONTHECHANGINGNATUREOFCORPORATEHIERARCHIESRaghuram G. Rajan and Julie Wulf*AbstractUsing a detailed database of managerial job descriptions,reportingrelationships, andcompensationstructures inover 300largeU.S. rms, we nd that rm hierarchies are becoming atter. The numberof positions reporting directly to the CEO has gone up signicantly overtime while the number of levels between the division heads and the CEOhasdecreased. MoreofthesemanagersnowreportdirectlytotheCEOand more are being appointed ofcers of the rm, reecting a delegationof authority. Moreover, division managers who move closer to the CEOreceivehigherpayandgreaterlong-termincentives, suggestingthat allthisisnotsimplyachangeinorganizationalchartswithnorealconse-quences. Importantly, atteningcannot becharacterizedsimplyascen-tralizationordecentralization. Wediscussseveral possibleexplanationsthat may account for some of these changes.I. IntroductionECONOMIC theorists have long advocated a move awayfrom seeing the rm as a black box and toward focusingonitsinternal organizationinstead. Forexample, asWil-liamson (1981) argues, viewing the rm and its organizationas a governance structure rather than simply as a produc-tionfunctionwouldhelpusunderstandbetterthebound-aries between the rm and the market.Workfromthe1960sthroughtheearly1980s(see, forexample, Williamson, 1967; Calvo & Wellisz, 1978, 1979;Rosen, 1982) followed this approach by seeking to explainthesizeof rms as aconsequenceof thelimitations ongovernancethat canbeexertedbycorporatehierarchies.Broadlyspeaking, hierarchies emanate fromthe needtosupervise workers. Any manager has limited time to super-viseemployees,sohisspanofsupervisionwillbelimited(Calvo & Wellisz, 1979; Rosen, 1982), and the number oflayers in the organization will also be limited by the loss ofcontrolacrosslevels(Williamson,1967;Calvo& Wellisz,1978). As a bonus, this work also explains why moretalented employees will occupy higher positions in thehierarchybecause their effort affects more employees (seeCalvo&Wellisz, 1979; Rosen, 1982). Thusat once, twostylized facts about corporations are explainedthat largerrms paymanagers more, andthat wages goupas onemoves up the hierarchy.Sincethisearlywork, therehasbeenmuchmoretheo-reticalworktryingtoexplainotheraspectsofrmhierar-chies. Yet we dont have very many more stylized facts todiscipline the theory, despite the fact that corporations in theUnited States have been changing tremendously. Peripheralbusinesseshavebeendivestedascorporationsfocusmoreon core areas, and peripheral activities have been out-sourced [see, for example, the account in Powell (2001)]. Atthesametime, largecorporationshavebeenmergingatahistorically unprecedented rate (see Pryor, 2000). Evenwhile corporate boundaries are being redrawn, there is somesuggestion that the very nature of employment relationshipsis changing (see, for example, Osterman 1996; Holmstrom& Kaplan, 2001; Rajan & Zingales, 2000).General Electrics recent organizational changes illustratethe type of facts that might be of interest to organizationaltheorists. The former chairman of GE Capital, who reporteddirectly to the CEO, resigned from his position, and the fourbusinessunit headsstartedreportingdirectlytotheCEO.Jeffrey Immelt, the CEO of GE, explained the decision thus:The reason for doing this is simpleI want more contactwiththenancial servicesteams. . . . Withthissimpliedstructure,theleadersofthesefourbusinesseswillinteractdirectly with me, enabling faster decision making and exe-cution.1In this example, GEs organization became atter:the CEOs span of control (or the number of positionsreporting directly to the CEO) increased by 3 (owing to theloss of the chairman of GE Capital and the gain of four unitheads: consumer nance, commercial nance, equipmentmanagement, andinsurance), andtheaveragenumber ofreporting levels between the unit heads and the CEO in GEdeclined (see gure 1).Is this patternof changespecial toGE, or is it moresystematic?Perhapsacarefuldocumentationofwhatfun-damentally, if anything, haschangedincorporatehierar-chies will give us a newset of facts to explain, andhopefullyabetter waytounderstandtheboundaries be-tween the rm and the market. Certainly, we have learnt alot by trying to explain stylized facts about static differencesbetweenrms, andevenpast changes[forexample, Wil-liamsons(1975, 1985) workonthemovement fromtheU-formtotheM-formoforganization]. It istimetoaddmorefactstothetheoreticalmill,andtoofferpreliminaryexplanations for them.We examine how corporate hierarchies have changed inthe recent past. We use a detailed database of job descrip-tions of top managers, reporting relationships, and compen-Received for publication December 7, 2004. Revision accepted forpublication November 22, 2005.* GSB, University of Chicago; and Wharton School, University ofPennsylvania, respectively.Wearegrateful toKatieDonohueat Hewitt Associates, K. Subrama-nium, andTalhaNoorMuhammedforassistanceindatacollection.Wewouldliketothankseminarparticipantsat Wharton, theUniversityofChicago, Columbia University, the NBEROrganizational EconomicsConference,andtheHarvardBusinessSchoolStrategyConference,andespeciallyGeorgeBaker, Peter Cappelli, BrianHall, BrigitteMadrian,KevinMurphy, andJoel Podolny. Wulfacknowledgesresearchsupportfrom the Reginald H. Jones Center for Management Policy, Strategy andOrganizationat theWhartonSchool oftheUniversityofPennsylvania,and Rajan thanks the Center for Research on Securities Prices, the CenterfortheStudyoftheStateandtheEconomy, andtheNational ScienceFoundation for research support.1General Electric press release titled GE Announces Reorganization ofFinancial Services; GECapital toBecomeFour SeparateBusinesses,July, 26, 2002.The Review of Economics and Statistics, November 2006, 88(4): 759773 2006 by the President and Fellows of Harvard College and the Massachusetts Institute of Technologysation structures in over 300 large U.S. rms tracked over aperiod of up to 13 years. We focus on the seniormost levelsof the hierarchy: after all, it is the CEO and other membersof senior management who make resource allocation deci-sions that ultimately determine the rms performance (andmost obviously represent the managers in the theories).Wedocument that theatteningoftheseniormanage-ment hierarchy reported in the General Electric example iswidespread in the United States among leading rms in theirsectors.2Ourrst ndingisthat thenumberofmanagersreporting to the CEO has increased steadily over time, froman average (median) of 4.4 (4) in 1986 to 8.2 (7) in 1998.3We consider several simple explanations for the increase inCEO span of control including rm growth, addition of newpositions (such as the chief information ofcer), and merg-ers. Taken together, these explanations account for only partof the trend.Our second nding is that the depth, which is the numberof positions between the CEO and the lowest managers withprotcenterresponsibility(divisionheads), hasdecreasedby more than 25% over the period.4Moreover, the numberof division heads reporting directly to the CEO has tripled.One possible explanation of all this is that the organizationalhierarchy is becoming atter.Another possible explanation, however, is that fewer butlargerunitsarebeinggivenprotcenterresponsibility. Inother words, it may be that rms have regrouped units intolarger divisions so that division heads have become impor-tant enough to report to the CEO. But when we focus onlyondivisional manager positionsthat report over multipleyears(andthusareunlikelytobecreatedorevengreatlyaffectedbyorganizational restructuring), wendthat de-spitelittlechangeindivisionsize, thesepositionshaveahigher probabilityof reportingtotheCEO, aswell asashorter distance fromthe CEOon average, over time.Moreover, more of these positions are gettingincreasedauthoritybybeingdenominatedofcersoftherm. Sohierarchies do seem to be getting atter, even while author-ity is being delegated down the organization.One way organizations can become atter is by eliminat-ingintermediarypositionsbetweentheCEOanddivisionheads, as intheGEcase. Wendevidenceof this. Forinstance, thechiefoperatingofcer(COO), whotypicallystood between the CEO and the rest of the rm, is increas-ingly rare. The number of rms with COOs has decreasedby approximately 20% over the period.It is always possible that organizational structure is sim-ply a way of conveying status and is otherwise meaningless.For example, some sociologists argue that informal net-worksplayamuchmoreimportantrolethanformaltitlesand reporting relationships in determining informationowsanddecision-making. Toseewhetherthechangeinorganizationalformhaseffectsoutsidethemindsofman-agers, weexaminehowpaychanges withorganizationalstructure. Wendbothsalaryplus bonus andlong-termincentivesforadivisionalmanagerpositionincreaseasitgets nearer the top, even after correcting for other determi-nants of pay like the number of employees under thepositions supervision.In sum, the CEO seems to be reducing the organizationaldistance betweenhimandoperational managers suchasdivisionheads. Yet it does not appear he is completely2Based on a variety of statistical tests, we conclude that our sample isrepresentative of Fortune 500 rms. We discuss this in detail in section IIB.3Others have found, using smaller data sets and focusing on particularindustries, that the managers span of control seems to be increasing (see,for example, Scott, OShaughnessy, & Cappelli, 1996), but these studiestypically use an indirect measure of span (the number of managers at onelevel divided by the number of managers at the next level) and focus atlevelsbelowtheCEO. Our measureof CEOspanispotentiallymoreprecise, because we know who reports to the CEO.4Baker, Gibbs, and Holmstrom (1994) nd that the number of levels isconstant over time for the single rmin their study. Using detailedpersonnel records, they infer the number of levels from information aboutmoves betweenjobtitles andconsider all levels withinthe rm. Bycontrast, wefocusonlyonthelevelsbetweenseniormanagementposi-tions, but have a potentially more accurate measure because of informa-tion on reporting levels.FIGURE 1.GENERAL ELECTRIC: CHANGE INCEOSPAN OF CONTROL ANDORGANIZATIONAL LEVELS, JULY2002THEREVIEWOFECONOMICSANDSTATISTICS 760takingoverthedecision-makingpowerorthesupervisorypower of the eliminated intermediate layers of management.Closer divisional managersaregettingmoreauthoritybybeing appointed ofcers, a fact further corroborated by theirhigher pay. Moreover, their greater long-termincentivessuggest that their decisionsarebeingguidedbystrongerincentive pay rather than close monitoring. Though the CEOmaybeincloser contact withoperational managersthanbefore, he is simply not trying to substitute himself for theeliminated layers.Taken together, these ndings suggest that corporatehierarchies are becoming atter. It is not easy to ascribe thelabel centralizationordecentralizationtothis. Ontheone hand, the CEOis gettingdirectlyconnecteddeeperdown in the organization, a form of centralization. Increas-ing span of control suggests he is more directly involved indecision-making across a greater number of organizationalunits. Onthe other hand, decision-makingauthorityandincentivesarealsobeingpushedfurtherdown, aformofdecentralizationor, using the jargon, empowerment.What could explain the ndings? Three possible classesof explanations are (i) an increase in the competitiveness ofthe external environment, forcing the need for a morestreamlined organization, (ii) an improvement in corporategovernance, forcing CEOs to eliminate excessive layers ofmanagers built upduringpast empirebuilding, and(iii)advancesininformationtechnologythatexpandtheeffec-tive span of control of top managers. Although we will layouttherationaleforeachclassofexplanations,aswellaspossiblewaystotest them, detailedtestingisbeyondthescope of this paper.Weare,ofcourse,notthersttopointoutthatorgani-zations might be becoming atter. This certainly is conven-tional wisdomin the business press, and a number ofacademic papers have also mentioned it (see, for example,Powell, 1990; Osterman, 1996; Scott, OShaughnessy, &Cappelli, 1996; Useem, 1996). However, no research we areaware of systematically quanties these changes, correlatesthemwithcompensation, anddiscussespossibleexplana-tions of the observed patterns.Theremainder of thepaper is outlinedas follows. Insection II, we describe the data, in section III we establishthefacts, andinsectionIVwediscusspossibleexplana-tions. We conclude in section V.II. Data DescriptionA. The SampleEmpirical work on the organizational structure of rms islimited. This is primarily due to the lack of detailed infor-mation on structures and the difculty in nding measuresthatallowcomparisonsacrossrms. Asaresult, previousresearchreliesoneitherdetaileddatasetsofasinglerm[such as the personnel records in Baker et al. (1994)] or lessdetaileddataonasmaller sampleof rms [suchas thecompensation survey data on 11 insurance rms in Scott etal. (1996)].5Thesestudies typicallyinfer thenumber oflevelsinthehierarchyfrompromotionsbetweenpositionsor measurethespanof control interms of ratios of thenumbers of employees at different organizational levels. Bycontrast, the primary data set used in this study includes apanel of more than 300 publicly traded U.S. rms over theyears 19861998, spanning a number of industries. We usedetailedinformationonjobdescriptions, titles, reportingrelationships, and reporting levels of senior and middlemanagement positions that allow us to characterize organi-zational structuresofrmsinapotentiallymoreaccurateway than previous research.The primary data used in this study are collected from acondential compensation survey conducted by Hewitt As-sociates, a leading human resources consulting rm special-izing in executive compensation and benets.6The survey isthe largest private compensation survey (as measured by thenumber of participating rms) and is comprehensive in thatit collects data on more than 50 senior and middle manage-ment positions including both operational positions (such asthechiefoperationsofceranddivisional CEO)andstaffpositions(suchasthechief nancial ofcer andheadofhuman resources).7The survey typically covers all thepositions at the top of the hierarchy and a sample ofpositionslowerdown. Anobservationinthedataset isamanagerial positionwithinarminayear. Thedataforeach position include all components of compensation,including salary, bonus, restricted stock, stock options, andotherformsoflong-termincentives(suchas,performanceunits). Toensureconsistencyinmatchingthesepositionsacrossrms, thesurveyprovidesbenchmarkpositionde-scriptions andcollects additional data for eachposition,including the job title, the number of employees under thepositionsjurisdiction,thetitleofthepositionthatthejobreportsto(thatis,thepositionsboss),andthenumberofreporting levels between the position and the board ofdirectors.We believe the survey data are accurate, for severalreasons. First, Hewitt personnel areknowledgeableaboutsurveyparticipants, becausetheyaretypicallyassignedtospecic participants for several years. Furthermore, al-though the participating rms initially match their positionsto the benchmark positions in the survey, Hewitt personnelfollow up to verify accuracy and spend an additional 810hours on each questionnaire, evaluating the consistency ofresponseswithpublicdata(suchasproxystatements)and5Thereareseveral earlyempirical papersonorganizational structureusingcross-sectionaltechniques(forexample, Child, 1973;Pughetal.,1968).6Wediscussbelow(sectionIIB)somepossibleselectionissuesasso-ciated with this sample.7Inthisstudyweuseasubset of thesurveysbenchmarkpositions:position descriptions are listed in the appendix.THEFLATTENINGFIRM 761across years.8Participants use the survey results to set paylevels and design management compensation programs, anindication that they believe others treat the survey seriously.9In table 1, we present descriptive statistics for the rms inthe sample. The data set includes more than 300 rms; theexact number varies over the period, as rms enter and exitas survey participants. We report statistics on both the wholesample(unbalanced) andthesubset of 51rms that areincludedinthesamplefortheentire13-yearperiod(bal-anced).Thermsinthesamplearelarge, publiclytradedU.S. rms that are well establishedandprotable, withaverage size of approximately 47,500 employees, age of 85years since founding, and return on sales of 19% (see table1A). The typical rm in the sample is thus a large, mature,stable rm, not one whose organizational structure is likelyto be in ux. The sample rms span many industrial sectorsof the economy, with some concentration in the food, paper,chemical, machinery, electrical, transportationequipment,instrumentation, communications, and utilities industries(table 1B).B. Sample RepresentativenessClearly, animportant questionindatasetssuchasthisone is that of sample selection: whether the rms in the dataset are or are not representative of, employers of similar sizeintheirindustry. Thesurveyparticipantsaretypicallytheleaders in their sectors; in fact, more than 75% of the rmsin the data set are listed as Fortune 500 rms in at least oneyear, and more than 85% are listed as Fortune 1000 rms.These rms represent a signicant fraction of the activity ofpublicly traded rms in the United States. Based on all rmscoveredinStandardandPoorsCompustat databaseovertheperiodof study, thesurveyparticipantsrepresent ap-proximately 33%of employees, 30%of sales, 20%ofassets, and 40% of market value. If we limit the analysis tomanufacturingrms, the Hewitt rms represent 42%ofemployees, 38% of sales, 39% of assets, and 52% of marketvalue.In general, Hewitt survey participants also participate inothercompensationconsultingrmsurveys(HayAssoci-ates, Mercer, orTowersPerrin, tonameafew)anddosoprimarily to receive information about pay practices to useasacompetitivebenchmarkinevaluatingtheirowncom-pensation programs.10It is important to note that the sample8For example, a rst-time participating rm reads the position descrip-tions and is shown examples like the one in gure A1 in order to matchtheir positions to those covered in the survey.9There may be incentives for survey participants to misreport pay datain their survey responses for positions other than those reported in proxystatements. However, severalfactsoffsetthelikelihoodofthispractice.First, for Hewitt clients, pay comparisons between the client and surveyaverages (excluding the client data) are provided to the board of directors,making it less likely that clients would misreport their own pay. Second,thesesurveysarecompletedbythermscompensationanalyst, anditwould require a signicant amount of internal coordination among severalmanagers to intentionally misreport. Finally, the most important measuresin this papernamely, proxies for span and depth of the hierarchyarentreportedtosurveyparticipantsandareonlyusedbyHewitttoimproveaccuracy in benchmarking positions across rms.10The value of a compensation survey to a participating rm depends onhow representative it is of rms that the participant competes with in theexecutive labor market.TABLE 1.DESCRIPTIVE STATISTICSWHOLE SAMPLE (UNBALANCED)AND BALANCED SAMPLEA. Firm Characteristics of SampleVariableWhole Sample (Unbalanced) Balanced Sample (N 51)Mean STD N Mean STD N1986 1998 1998 (rm-yr) 1986 1998 1998 (rm-yr)Size (000s emp.) 47.45 49.49 92.27 3270 85.86 73.81 106.52 645Protability 0.167 0.189 0.098 3292 0.162 0.201 0.093 640Age (years) 84.8 40.81 3292 105.3 33.47 640Number of segments 2.99 3.21 1.85 2519 3.29 3.91 1.86 609Inst. shareholders (%) 51.6 61.7 15.9 2393 51.2 60.9 11.2 510B. Industry Characteristics of Firms in SampleIndustry(2-digit SIC)Distribution of Sample by 2-digit SIC CodeIndustry (2-digit SIC)Distribution of Sample by 2-digit SIC CodeWhole Sample Balanced Sample Whole Sample Balanced SampleN(rm-yr)% ofSampleN(rm-yr)% ofSampleN(rm-yr)% ofSampleN(rm-yr)% ofSampleFood (20) 202 6.0 78 12.0 Transp. equip. (37) 232 6.9 78 12.0Paper (26) 129 3.9 26 4.0 Instrumentation (38) 133 4.0 26 4.0Chemical (28) 467 13.9 169 26.0 Communications (48) 161 4.8 13 2.0Machinery (35) 340 10.1 26 4.0 Utilities (49) 399 11.9 13 2.0Electrical (36) 153 4.6 26 4.0 Other 1,134 33.9 195 30.0Notes: Whole sample includes all rms in the sample. Balanced sample includes rms that appear in the sample over the 13-year period. Panel A: Protability is dened as EBITDA/sales. Age is dened as numberof years since founding as listed in the Directory of Corporate Afliations. Number of segments is that reported in the Business Segment le of Compustat. Institutional shareholders represents the percentage ofshares held by institutions as reported by Spectrum.THEREVIEWOFECONOMICSANDSTATISTICS 762includesmanymorermsthanHewittsconsultingclientbase; at least 50% of the rms are survey participants withno client relationship to Hewitt.11We evaluate the representativeness of our sample bycomparing key nancial measures of our survey participantswith a matched sample fromCompustat. We begin bymatching each rm in the Hewitt data set to the Compustatrm that is closest in sales within its two-digit SIC industryinthe year the rmjoins the sample. We thenperformWilcoxonsignedranktests tocomparetheHewitt rmswiththematchedrms. AlthoughthermsintheHewittdataset are, onaverage, slightlylarger insalesthanthematchedsample, wefoundnostatisticallysignicant dif-ference in employment and protability (return on sales).12We also found no statistically signicant difference in salesgrowth, employment growth, orannual changesinprot-ability for all sample years. In sum, though the Hewitt rmsare larger (measured by sales) on average than the matchedsample, there is little additional evidence that these rms arenot representative of the population of industrial rms thatare leaders in their sectors.13To sum up, the survey sampleis probably most representative of Fortune 500 rms.C. Measures of Organizational StructureOur studyfocuses ontwomeasures of organizationalstructure: the breadth and depth of the hierarchy. Breadth isrepresented by the CEOs span of control (CEO Span) andis dened as the number of positions reporting to the CEO.Because we know the title of the position that each positionreports to (the positions boss), we can determine the posi-tions that report directly to the CEO.14Our other measure,depth, represents a vertical dimension of the hierarchy andis dened as the number of positions between the CEO andthedivisionalCEO.Inthesurvey,adivisionisdenedasthelowestlevelofprotcenterresponsibilityforabusi-ness unit that engineers, manufactures andsells its ownproducts.Wefocusonthedivisional CEOposition(hereafterre-ferred to as divisional manager) for two reasons: (i) it is thepositionfurthest downthehierarchythat ismost consis-tentlydenedacrossrms,and(ii)itisinformativeabouttheextenttowhichresponsibilityisdelegatedintherm.FigureA1(at theendof thepaper) displays an(edited)examplefromthesurveythatdemonstratestoparticipantshowtodeterminethenumberofreportinglevelsforeachposition. The management reporting relationships areclearly illustrated with the line of authority starting with theCEO as the most senior position, moving down to the COO,thegroupCEO, thedivisional CEO, andnallytheplantmanagerasthemost juniormanagement position. Inthisexample, our measureof depthequals 2therearetwopositions between the CEO and the divisional manager.Other positions that might be informative about the depthofthehierarchyaregroupCEOs(managerswithmultipleprotcenterresponsibility)andplantmanagers(managerswithbudget or cost center responsibility), but there arelimitations to using either. Group CEOs are dened on thebasis of their position in the hierarchy (proximity to CEO orCOO). Hence it is harder toinfer facts about depthorresponsibilityfromtheir position. Bycontrast, divisionalmanagers are dened on the basis of their responsibility, andhence we can infer more about hierarchies from where theyareplaced. Unfortunately, though, thedenitionof plantmanagers is not consistent across industries, especiallywhen one moves from manufacturing to service rms.15The survey data are supplemented with information fromseveral other data sets (Compustat for nancial and segmentinformation; SecuritiesDataCompanyformergers; Spec-trumfor institutional shareholdings; Gompers, Ishii, andMetricks (2003) index, basedonIRRCdata, for gover-nance information; and Directory of Corporate Afliationsforyearoffounding). WhereasthesurveyisconductedinApril of each year and the organizational data describe thermintheyearofsurveycompletion, somestatistics(in-cludingthenumberofemployeesinadivision)representtheendofthemostrecentscalyear. Tomaintainconsis-tency,wematchthesupplementaldatasetsusingtheyearprior to the year of the survey. Finally, not all variables are11One concern about sample selection bias is that rms participating incompensation surveys (Hewitts or any others) may be inclined to adoptmoremoderncompensationpractices, includinggreater incentivepay.This is certainlypossible. However, it is highlyunlikelythat surveyparticipants attentheir organizational structureinresponsetosurveydata. Asmentionedinanearlierfootnote, theinformationonreportinglevels in the survey is collected to ensure proper benchmarking ofpositions across rms, and no information about CEO span of control ororganizational levels of divisional managers is provided to rms in returnfor participating.12The Hewitt rms are larger in sales than the matched sample of rmsbecause in a number of the cases, the Hewitt rm is the largest rm in theindustry, thus forcing us to select a matched rm smaller in size.13Wealsocalculatenancial measuresfor thesampleof Compustatrms with 10,000 employees or more over the period from 1986 to 1998(excluding rms operating in nancial services). We nd that, on average,survey participants are more protable, but growing at a slower rate, thanthoseinthesampleof largeCompustat rms. Specically, thesampleaverage return on sales for survey participants is 17.8%, versus 15.7% forthe sample of large Compustat rms, and the average sales growth is 5.7%versus 7.4%. This is consistent with our observation that the rms in oursamplearelikelytobeindustryleaders(henceslightlymoreprotable)and also large (hence with slightly slower growth). There is no reason whythis should dramatically skew the inferences from the sample.14Becausethesurveyisbasedonbenchmarkjobs, it ispossiblethatnonstandard positions are excluded from the survey or added over time.Companies may differ systematically as to the percentage of managementpositions that are benchmark jobs, and this might bias our measure of thespan. Because, however, the positions reporting to the CEO are the mostsenior positions and the primary focus of the survey over the period, weexpect the bias to be minimal.15Theclassicdistinctionbetweenorganizationsthat areorganizedbyfunctionandbydivisionswithprot-centerauthorityislessrelevantinthis sample of rms. In fact, in this large sample of rms, pure functionalorganizations appear to be uncommon. Using the reporting of divisionaland subsidiary data from the Directory of Corporate Afliations, we wereable to categorize the structure of just over half of the sample rms. Onlyone rm could be classied as a pure functional organization. In general,information about organizational form did not add explanatory power toour analysis.THEFLATTENINGFIRM 763available for all positions, rms, andyears, anddue tolimitations in matching with the supplemental data sets, oursamples are smaller for some parts of the analysis.III. The FactsA. Increasing SpanHavingdescribedthedataandtheirsources,letusnowexaminehowrmhierarchiesarechangingovertime. Intable 2, we describe how the number of positions reportingdirectlytotheCEO(that is, CEOSpan) movesover theperiod. The number of positions reporting has gone up froma mean (median) of 4.46 (4) in 1986 to 6.79 (6) in 1998, anincrease of approximately 50%. One might worry that someof the change is induced by changes in the composition ofour sample over time. If we restrict ourselves to the 51 rmsthat appear throughout the 13 years of our panel, however,the change is even more dramatic. From a mean (median) of4.39(4)itgoesupto8.16(7),anincreaseof86%. Alter-natively, in the last three columns in table 2 we report theaverage annual change in span for the rms that appear fortwo consecutive years in the data set. Cumulating thatannual average change in span, we get a total of 2.42 overthe 13-year period.Is this simply hardwired? Could increasing CEO spanreect the natural growth of rms? No, because rms couldaccommodate growth by adding layers to the hierarchyrather than increasing the span of control, and because rmshavenot grownsignicantlyoverthisperiod. Infact, theaverage size of the 51 rms appearing throughout, as mea-sured by the number of employees, has fallen from 86,000in 1986 to 74,000 in 1998 (see table 1A). In the unbalancedpanel, thesizeof rms is roughlyconstant over timeapproximately 48,000 in both 1986 and 1998. When we sortrmsintoquartilesbasedonthegrowthinthenumberoftheir employees over the sample, we do not nd any clearpattern in span across the quartiles (not reported in table).16An obvious question is whether the growth in CEO reportsis a result of mergersare rms simply stitched together attheseamsunder acommonCEO, andwouldthemergerwave account for our ndings? To address this we drop fromthebalancedsampleallrmsthatundertookoneormoresignicant acquisitions (amountingtomorethan20%ofassets in any year) in the previous 3 years. CEO reports stillincrease from 4.4 in 1986 to 8.2 in 1998. We also drop fromthe sample all rms that undertook signicant acquisitionsat any time during the period covered. Again, CEO reportsincrease from 4.4 in 1986 to 8.2 in 1998.Another obvious question is whether the growth in CEOreports is duetoincreases indiversication. Infact, theaveragenumberofsegmentsreportedbyCompustat (onemeasure of diversication) for the balanced sample in-creasesfrom3.3in1986to3.9in1998(table1A).How-ever, inarm-xed-effects regressionof thenumber ofCEO reports on (the logarithm of) the number of employees,the number of segments, and a trend variable, the coefcienton the number of segments is insignicant, suggesting thatthe increase in span is not primarily related to increases indiversication.1716Firms may grow in size or complexity without adding more workersfor example, through outsourcing. To evaluate this, we estimate allregressions andreplace rmanddivisionemployment withrmanddivision sales, respectively. We nd that our results are generally robustusing this alternative measure of size, with the rare exception noted.17One might even argue the reverse: the CEO plays a coordinating role,so one would expect more reports to the CEO when there is more of a needfor coordinationbetweenvariousbusinesssegments, that is, whentherms segments or divisions are more related. This conjecture too is notborne out in the data. Using data on a divisions industry and the share ofemployees in a two-digit industry within the rm, we calculate a Hern-dahl index (HHI) for the rms presence in different industries as a morerenedmeasureofrelatedness. Inarm-xed-effectsregressionoftheTABLE 2.ORGANIZATIONAL SPAN (SPAN): NUMBEROF POSITIONS REPORTINGTOTHE CHIEF EXECUTIVE OFFICERYearWhole Sample (Unbalanced) Balanced Sample (N 51) Sample with 2 Consecutive YearsMean Median STDN(rms) Mean Median STDChangesMeanChangesSTDN(rms)1986 4.46 4 2.05 210 4.39 4 1.891987 4.61 4 2.12 231 4.65 5 1.97 0.21 1.62 1881988 4.75 4 2.67 236 4.65 4 2.09 0.11 1.72 2031989 5.07 5 2.53 228 4.71 5 1.95 0.14 1.99 2001990 4.91 5 2.60 276 4.98 5 1.74 0.03 1.88 2101991 4.81 4 2.96 289 5.25 5 2.08 0.05 2.17 2491992 4.89 5 2.50 290 4.96 5 2.12 0.02 1.73 2601993 5.01 5 2.24 304 5.53 5 2.10 0.10 1.93 2611994 5.38 5 2.45 298 5.82 5 2.15 0.33 1.82 2561995 5.65 5 2.54 288 6.47 6 2.64 0.39 2.08 2501996 5.46 5 2.56 280 6.31 6 2.32 0.19 2.07 2431997 6.10 6 2.94 248 7.08 6 2.75 0.58 2.37 2231998 6.79 6 3.90 213 8.16 7 4.02 0.75 3.39 183Average 5.21 5 2.70 261 5.61 5 2.58 0.19 2.10 222N (rm-yr) 3,391 2,733Notes: Whole sample includes all rms in the sample. Balanced sample includes rms that appear in the sample over the 13-year period. Sample with 2 consecutive years includes all the rms in the sample forthe year and the year prior. Changes is the change in span between year t and year t 1.THEREVIEWOFECONOMICSANDSTATISTICS 764As an aside, in what follows we have the option ofreportingdata for the balancedpanel of rms reportingthroughout or also reporting data for the unbalanced panel.The balanced panel has the virtue of allowing comparisonsto be made for the same rms over time. It has the demeritof focusingonlyonsurvivors andtherefore introducingpotential biases. Fortunately, the patterns from the balancedpanel look qualitatively like those in the unbalanced panel.Couldtheincreasedspanbearesult ofthecreationofnew positions such as chief information ofcer (CIO) or theincreasing importance of existing positions such as head ofhumanresources (HHR), whonowjoinmoretraditionalpositions such as chief nancial ofcer in reporting directlyto the CEO? The data do not support this explanation.18Intable 3, we report for the balanced panel the average numberof direct reports to the CEO from a particular position. EachCEO had, on average, 0.02 CIOs and 0.37 HHRs reportingin 1986. By 1998, each CEO had 0.18 CIOs and 0.65 HHRsreporting. Thus these two positions account for only approx-imately 0.45 of the increased reports to the CEO. Where dothe rest of the reports (equal approximately to 8.16 4.39 0.45 3.32) come from?The answer seems to be that they come from traditionallymore junior positions. The average number of group man-agersreportingdirectlytotheCEOwentupfrom1.03in1986 to 1.73 in 1998 (see table 3). The number of divisionmanagers reporting directly to the CEO went up from 0.21in 1986 to 0.95 in 1998. Thus the increase in direct reportsfrom positions traditionally lower down in the organizationaccounts for approximately 45% of what is unaccounted for(0.70 0.74 1.44 of 3.32).19The number of divisional manager positions reported bysurvey participants has increased over time. So perhaps asimportant as knowing the average number of group ordivisional managers who report to the CEO is knowing whatfraction of the group or divisional managers covered by thesurvey report to the CEO. Call this the probability ofreporting to the CEO. For group managers this probabilityincreased slightly over the period, from 0.43 in 1986 to 0.61in 1998 (see table 3). The probability that a divisionalmanager reportstotheCEOconsistentlytrendedupwardover the period, from 0.05 in 1986 to 0.31 in 1998.Parenthetically, sometraditionallyseniorpositionshavealsobecomecloser totheCEO. Whereas 67%of CFOsreported to the CEO in 1986, 90% did so in 1998. A similarpatternisseenfor thegeneral counsel. Lawandnanceseem to have become more important!B. Decreasing Depth and Increasing EmpowermentEven though only some division managers report directlyto the CEO, the trend for them to be closer to the CEO ismore general. Table 4Bcolumn (ii) (balanced sample),suggests that the average depth at which the division man-ager islocatedbelowtheCEO(thenumber of managersbetween the CEO and the division manager) has fallen, fromnumber of CEO reports on (the logarithm of) the number of employees,HHI, andatrendvariable, thecoefcient onHHIisinsignicant, sug-gesting that the increase in span cannot be explained by a greater need forcoordination.18Thechief informationofcer (CIO, position8intheappendix) isdened as the highest level of operating management over the combinedfunctions of programming, data processing, machine operation, and sys-temsworkrelatedtodataprocessing. Headofhumanresources(HHR,position 7 in the appendix) is dened as the head of all human resourceswithresponsibilityfor establishingandimplementingcorporation-widepolicies.19Some functions have increased considerably in importance. Only 0.2publicrelationsofcersreportedtotheCEOin1986, andthenumberincreased to 0.57 in 1998. Corporate research and development positionsandmanufacturingpositionsaccount for approximately0.20of there-maining increase in the number of CEO reports.TABLE 3.ORGANIZATIONAL SPAN: REPORTSTOTHE CEOBY POSITION (BALANCED SAMPLE; N 51)YearAverage NumberCorporate Staff Positions Intermediaries Unit HeadsChiefInformationOfcerHumanResourcesChiefFinancialOfcerGeneralCounselStrategicPlanningPublicRelationsChiefOperatingOfcerChiefAdministrativeOfcerGroup Manager Division ManagerAvg. No. Probability Avg. No. Probability1986 0.020 0.373 0.667 0.667 0.275 0.196 0.549 0.392 1.026 0.434 0.205 0.0521987 0.078 0.451 0.686 0.667 0.255 0.235 0.529 0.353 0.897 0.432 0.340 0.0971988 0.039 0.490 0.686 0.686 0.255 0.294 0.549 0.392 0.789 0.417 0.213 0.0631989 0.020 0.490 0.706 0.725 0.255 0.333 0.510 0.314 0.947 0.407 0.205 0.0731990 0.039 0.510 0.667 0.725 0.294 0.431 0.588 0.333 0.970 0.419 0.229 0.0841991 0.039 0.549 0.706 0.745 0.314 0.451 0.529 0.392 1.143 0.490 0.255 0.1081992 0.020 0.471 0.745 0.667 0.255 0.294 0.549 0.412 1.029 0.431 0.298 0.1211993 0.039 0.529 0.863 0.784 0.255 0.275 0.412 0.314 1.353 0.545 0.609 0.2151994 0.039 0.549 0.882 0.784 0.255 0.275 0.392 0.353 1.472 0.583 0.783 0.2131995 0.039 0.627 0.902 0.784 0.275 0.353 0.392 0.353 1.737 0.619 0.860 0.2131996 0.039 0.667 0.961 0.843 0.235 0.314 0.412 0.275 1.721 0.556 0.581 0.1791997 0.078 0.706 0.941 0.902 0.235 0.412 0.431 0.275 2.051 0.670 0.535 0.1591998 0.176 0.647 0.902 0.961 0.392 0.569 0.451 0.294 1.733 0.606 0.953 0.314Notes: Balanced sample includes rms that appear in the sample over the 13-year period. Positions are described in the appendix. For the group and divisional manager positions, the averages and probabilitiesare calculated for the subset of rms reporting these positions. Probability is the fraction of group or divisional manager positions reported by the survey that report to the CEO.THEFLATTENINGFIRM 7651.58in1986to1.18in1998,approximately25%.20Inter-estingly, thecorrelationbetweenCEOSpanandDepthissignicantlynegative(correlation0.27forthewholesample). Wider organizations are also less tall, so that, put ina time series context, organizations are becoming atter. Inwhat follows, we will focus on CEO Span as a measure oforganizational structure (because we believe it is morecomprehensively reported), though we will use Depth wher-ever appropriate.Perhaps then the increasing number of reports to the CEOreects restructuring of business units: Perhaps prot centerresponsibility has been taken away from smaller units, andtheyarenowpart ofalarger, moreimportant unit whosemanager is, not surprisingly, closer totheCEOandnowmay even report directly to him. Again, this hypothesis doesnot seemconsistent withthedata. Theaveragesizeof adivision (the lowest level of prot center responsibility) hasdecreased from approximately 6,000 employees in 1986 to4,700 employees in 1998 [see table 4B, column (iii)].Of course, theremaybeasimpler explanationfor ourndings. The survey is not exhaustive, except at the highestlevels in the organization. Perhaps, as the survey expandedover time, it picked up lower, more obscure divisionalmanager positions. Thiswouldexplainwhydivisionsaregettingsmaller (but not whytheir depthis decreasing).Nevertheless, even the premise is incorrect: the survey hasexpandedinthenumber of divisional manager positionsreported but not in the fraction of the rm covered. For theconstant sample, we calculate the ratio of the total numberofemployeesunderdivisionalmanagerpositionssampledby the survey to the total number of employees in the rm.As table 4B indicates, this ratio was 0.42 in 1986 and 0.4 in1998. The coverage of the survey has not changed signi-cantly.21As yet, we cannot be sure whether the existing divisionalmanager positionsbecamecloser totheCEOor whetherorganizational changeresultedinnewdivisional managerpositions that were closer to the CEO. For example, if largerms started outsourcing more of their activities, new divi-sional managers might have been put in charge of units thatwere not large as measured by personnel, but were only thetip of a vast outsourced operation. It would not be surprisingthenthattheseimportantmanagerswouldbeclosertotheCEO.Onewaytogetatthisistofollowthesamedivisionalmanagerpositionovertime. Fromtheannualsurveys, weidentied which divisional manager positions were reportedmultiple times over the years. Focusing only on thesepositions, we regress attributes of the position(what itsdepth is, whether it reports to the CEO) against the size oftherm, thesizeof thedivision, year indicators, andanindicator for the position. These regressions should beviewedasattemptstoestablishpartial correlationsratherthan as implied causal relationships. Signicant coefcientestimatesontheyear indicatorswouldonlysuggest that,keepingthe other attributes of a positionapproximatelyconstant, its place in the organizational hierarchy did changeover time.The regressionestimates are reportedintable 5. Thestandard errors for the reported estimates are clustered at therm level, addressing the concern that division observations20In the last column in table 4 we report the average annual change indepth for the set of rms that appear for two consecutive years in the dataset. Cumulating that average change in depth for this set of rms, we get0.03 over the 13-year period.21Asimilar conclusion is reached if one examines the coverage of grouppositions reported (results available on request from the authors).TABLE 4.DESCRIPTIVE STATISTICSFIRMAND BUSINESS-UNIT (DIVISION) CHARACTERISTICS (MEANSAND CHANGES)YearA. Whole Sample (Unbalanced) B. Balanced Sample (N 51)Sample with 2ConsecutiveYears: (i) (ii) (iii) (iv) (v) (i) (ii) (iii) (iv)Firm Size(000s empz.) DepthDivision Size(000s empz.)DivisionCoverageN(rms)Firm Size(000s empz.) DepthDivision Size(000s empz.)DivisionCoverageDepth Changes(Mean)1986 47.5 1.49 3.8 0.53 210 85.9 1.58 6.0 0.421987 43.4 1.39 3.5 0.68 231 82.8 1.45 5.9 0.38 0.061988 42.0 1.43 3.4 0.46 236 84.3 1.51 5.2 0.38 0.001989 46.2 1.34 3.3 0.44 228 86.8 1.46 5.2 0.36 0.091990 44.7 1.28 3.1 0.39 276 86.2 1.36 5.1 0.33 0.051991 42.1 1.26 3.1 0.40 289 86.9 1.33 4.2 0.35 0.051992 41.3 1.29 3.1 0.37 290 83.2 1.35 4.4 0.33 0.031993 38.9 1.19 2.8 0.37 304 81.6 1.20 4.6 0.33 0.041994 41.1 1.08 3.1 0.42 298 81.8 1.19 5.1 0.37 0.051995 39.3 1.09 3.4 0.41 288 81.5 1.25 4.8 0.33 0.011996 42.6 1.14 3.6 0.43 280 79.6 1.30 5.5 0.37 0.011997 45.2 1.18 3.3 0.38 248 75.4 1.41 2.8 0.34 0.021998 49.5 1.14 3.7 0.39 213 73.8 1.18 4.7 0.40 0.06Average 43.1 1.26 3.3 0.43 261 82.7 1.36 4.9 0.36 0.03Notes: Whole sample includes all rms in the sample. Balanced sample includes rms that appear in the sample over the 13-year period. Sample with 2 consecutive years includes all the rms in the sample forthe year and the year prior. Firm (division) size is the number of employees in the rm (division) in thousands. Depth is dened as the number of positions between the CEO and the divisional manager (see gure2 for an example). Division coverage is dened as the ratio of the number of employees under divisional manager positions sampled by the survey to the total number of employees in the rm. Depth changes isdened as the depth in year t minus depth in year t 1.THEREVIEWOFECONOMICSANDSTATISTICS 766may not be independent across divisions within a rm.22Incolumn (i), the dependent variable is the depth of thespecic position (DDEPTH). We nd negative coefcientson all year indicators, with a trend of increasingly negativecoefcients over time. That is, division depth is decreasing,anddivisional managerpositionsaregettingclosertothetop. In column (ii), the dependent variable is 1 if thepositionreportstotheCEOdirectlyand0otherwise. WendthattheprobabilityofreportingtotheCEOincreasesover time, astheyear indicatorsbecomelarger over theperiod. Also, thenumberofemployeesunderaparticulardivisional managerpositiontrendsdownwardslowly(ap-proximately 1% every year). This suggests that even thoughthe structure of the division has not changed drastically overtime, its head has moved nearer the top. The organizationalhierarchy is indeed becoming atter.Finally, a direct measure of responsibility is whether theholder of a position is designated an ofcer of the corpora-tion: ofcers of the corporation are determined by both theindividuals authority and the nature and extent of theindividualsduties.23Incolumn(iii)oftable5,thedepen-dent variableiswhether thedivisional manager isdesig-natedanofcer. The year coefcients exhibit a broadlyincreasing trend over the entire sample, with the yearcoefcients averaging 0.014 in the rst third of the sampleyears (19871890), and 0.053 in the last third (19951998).Although only one of the year coefcients in the last third issignicantlydifferentfrom0,collectivelytheyaregreater22Clustering standard errors at the rm level instead of the division leveladdressesthepossibilitythat rmshavecertainrules(orstandards)bywhich they place all of their managers. In this case, the different positionsin a rm are not independent. Clustering by rm is a more conservativetest and particularly important if there is a lot of covariance between thepositions of managers in the same rm. In addition to clustering by rm,weestimateregressionsthatadjuststandarderrorsforserialcorrelation(AR1) and heteroskedasticity across division manager positions. Becausethe statistical signicances of the coefcients are similar for the twoapproaches, we choose to report standard errors clustered at the rm level.23ThetermofcerisdenedbytheSecuritiesandExchangeCom-mission in Section 240.16 (rules governing insider trading) as an issuerspresident, principal nancial ofcer, principal accountingofcer (or, ifthere is no such accounting ofcer, the controller), any vice-president ofthe issuer in charge of a principal business unit, division or function (suchassales, administration, or nance), anyother ofcer whoperformsapolicy-making function.TABLE 5.MEASURESOF EMPOWERMENTDIVISION-FIXED-EFFECTS REGRESSIONSIndependent variableDDEPTH CEORPT OFFICER(i) (ii) (iii)log(Division Employees) 0.074*** 0.019** 0.034***(0.020) (0.008) (0.011)1987 0.052 0.014 0.015(0.040) (0.015) (0.012)1988 0.034 0.012 0.018(0.058) (0.020) (0.016)1989 0.082 0.020 0.006(0.061) (0.020) (0.017)1990 0.152** 0.040* 0.017(0.060) (0.024) (0.020)1991 0.167*** 0.049** 0.030(0.060) (0.025) (0.020)1992 0.132* 0.047* 0.027(0.070) (0.024) (0.020)1993 0.195*** 0.067** 0.033(0.069) (0.027) (0.024)1994 0.254*** 0.095*** 0.041(0.074) (0.029) (0.026)1995 0.236*** 0.095*** 0.060*(0.076) (0.033) (0.034)1996 0.270*** 0.088*** 0.053(0.077) (0.032) (0.035)1997 0.285*** 0.098*** 0.052(0.081) (0.038) (0.041)1998 0.302*** 0.071* 0.045(0.088) (0.038) (0.036)Constant 2.077*** 0.066 0.036(0.143) (0.057) (0.077)Observations 10393 10428 10428Number of divisions 2360 2370 2370R-squared 0.73 0.58 0.77Dependent variables are DDEPTH (number of positions between CEO and divisional manager), CEORPT (divisional manager position reports to CEO), and OFFICER (incumbent in divisional manager positionis corporate ofcer).Notes: Includes all divisions in the sample that appear for at least two years. All specications include division xed effects. All variables have been Winsorized at the 99th percentile. DDEPTH is dened asthe number of positions between the CEO and the specic divisional manager position. CEORPT is a dummy variable equal to 1 if the divisional manager position reports directly to the CEO and 0 otherwise.OFFICER is a dummy variable equal to 1 if the incumbent in the divisional manager position is a corporate ofcer and 0 otherwise. log(Division Employees) is dened as the log of the number of employees inthe division. All specications report robust standard errors by clustering at the rm level. ***/**/* represent signicance at the 1%/5%/10% level.THEFLATTENINGFIRM 767than 0 at the 11% level.24By contrast, the year coefcientsin the initial third of the sample are not statistically differentfrom0.Theincumbentinthedivisionalmanagerpositionhas become somewhat more likely to be designated anofcer over time. Authorityandresponsibilityareindeedmoving further down.C. DelayeringThat theCEOis gettingmoredirectlyconnectedin-creasing span, reduced distance from managersis consis-tentwithanecdotalevidencethatorganizationshavebeengetting rid of entire layers of middle management. In gen-eral, it is hard to nd direct evidence of this at the level ofdetail our dataset offers onreportingrelationshipsthemere fact that positions disappear does not mean thatreporting has become more direct, for other positions couldplace themselves in the middle.25Not only do our data suggest that reporting has becomemore direct (for instance, that more division managers nowreportdirectlytotheCEO),buttheyalsosuggestthattheCEOis becomingmoredirectlyconnectedpreciselybe-cause of the elimination of intermediate positions: Considerthe position of the COO, who has historically served as anintermediarybetweentheCEOandtherestoftheorgani-zation.Astable3indicates, theaveragenumberofCOOreports to the CEO per rm has fallen from 0.55 to 0.45 overthe same period. The position of chief administrative ofcer(CAO) also seems to exhibit a similar decline. The declinein COOand CAOpositions that report to the CEOisprimarilybecause these intermediate positions are beingeliminated, and not necessarily because these ofcers haveless access totheCEO. Conditional onarmhavingaCOO, thepercentageof COOsthat reportedtotheCEOdidnt changeovertheperiod(verycloseto100%). Thissuggests that the decline in COO reports to the CEO is dueto the position being eliminated in the sample rms.In Table 6, column (i), we return to the unbalanced sampleand regress CEO Span against a constant, rm size (the log ofthe number of employees in the rm), rm, and year indicators.The trend in the coefcient estimates on the year indicators issignicantlypositive. CEOSpanincreases, onaverage, byapproximately 0.16 every year. In column (ii), we also includeanindicator for whether thermhas aCOOandanotherindicator for whether it has a CAO. The coefcients on the yearindicators fall slightly. Interestingly, the coefcient onthepresenceofaCOOisnegative, statisticallysignicant, andlarge (0.96). Assuming the COO always reports to the CEO,thiscoefcientsuggestshispresencereducesthenumberofCEO reports, because an average of 1.96 managers who wouldotherwise report to the CEO now report to him. In other words,the COO is truly an intermediary.26In column (iii) we regress Depth on rm size and on rmand year indicators, and we nd that the coefcients on theyearindicatorsbecomeincreasinglynegativeoverthepe-riod. Column(iv)suggeststhepresenceofintermediariesliketheCOOandtheCAO,increasetheaveragedepthatwhich division managers are positioned. If the COO stoodbetweentheCEOandallmanagers,thecoefcientontheCOO indicator would be 1. That it is lower suggests somedivisional managers do not report via the COO. Parenthet-ically, note that the coefcient onrmsize is positive,suggesting that growing rms seem to have greater depth.Although the coefcients on the year indicators fall whenweincludeindicatorsforthepresenceofthesepositions,theydonot becomeinsignicant. Thustheeliminationofthe COO and CAO positions accounts for part, but not all,of the trend. The attening of organizations is more than theelimination of just a few key intermediate positions.D. The Correlation with WagesAre increasing span and decreasing depth simply changeson paper with no real consequences whatsoever? Does theostensibleproximitytotheCEOsimplyreect agreaterdesireonthepart ofmanagersforstatus, withnogreaterincreaseinrealaccess?Evidencethatmoredivisionman-agers are becoming ofcers suggests that organizations arechanginginmeaningful ways. Andone strongpiece ofevidence suggests that these changes are not all form with-out any function: they seem to be accompanied by system-atic changes in pay.27The data set we have has extensive data on compensation.Wewouldliketoseeiftheatteningofthehierarchywehavedescribedhasanycorrelationwithpaypatterns. Tounderstand this, we examine the pay of divisional managers,who could be positioned anywhere from just below the CEOto far away.InTable7, wereporthowvariousattributesofthepaystructure for rms vary as depth decreases. The rst aspectofpayweconsideristhedivisionalmanagerssalaryandbonus. We regress the logarithm of this measure against thenumber of employees in the rm, the number of employeesin the division, the depth at which the division manager isplaced, and year indicators. The OLS estimate for the24This is one situation where including division sales, as we have done,instead of division employees reduces the signicance of the coefcients.Also, clustering by rm greatly reduces signicance relative to clusteringby division. When we cluster by division, seven of the year indicators arestatistically signicant.25Earlier work has inferred reporting relationships from organizationalpositions (managers in lower layers are assumed to report to managers inthe immediate higher layer). In this case, the elimination of some, but notall,positionsinintermediatelayerswouldnotallowustoconcludethatthere is a change in reporting relationships.26By contrast, the presence of a CAO increases CEO reports, but by lessthan 1. Because the CAO also typically reports directly to the CEO, thecoefcient estimateof 0.344suggeststhat theCAOalsointermediatesbetweenlower positions andthe CEO, but typicallyhas fewer directreports than the COO.27Larcker, Lambert, andWeigelt(1993)evaluatepaydifferentialsbe-tweendifferent positionsinarmshierarchy. However, theyhavenomeasureof CEOspanor thenumber of levelsbetweentheCEOanddivision managers.THEREVIEWOFECONOMICSANDSTATISTICS 768coefcient of depth[table7, column(i)] isnegativeandsignicant, suggestingthat for eachadditional layer be-tweentheCEOandthedivisionalmanager,thelogofthelatters salary and bonus falls by 0.14, which is 29.4% of itsstandard deviation. The coefcient continues to be negativewhenwe include xedeffects for the position[table 7,column(ii)], suggestingthat specic divisional managerpositions that are moving closer to the CEO over time getpaid more.We nd similar results when the dependent variable is theratioofthedivisionmanagerslong-termincentivepaytothevalueof salaryandbonus(typicallystockandstockoptions).28The OLS estimate [table 7, column (iii)] suggeststhatlong-termincentivepayfordivisionalmanagersgoesdown from a mean of 43.4% of salary and bonus to 37.1%for an additional layer between the CEO and the divisionalmanager. Includingdivisionxedeffectsdoesnot changethe estimate signicantly.29All this suggests that pay and incentives are adjusting tothe change in organizational structure. Even controlling forthe size of the division and the rm, division managers arepaid more as they move closer to the CEO. This is thereforenot thetraditional Calvo-Wellisz(1979) or Rosen(1982)effectit is not that thesemanagers arebecomingmoreimportant at the margin because they control larger opera-tions.Instead, it maywell be that theyare becomingmoreimportantbecausetheirdecision-makingissubjecttolesscloseoversight byintermediaries (thoughtomoredirectoversight by the CEO). In fact, as Aghion and Tirole (1997)argue, greater span may be a way for the CEO to commit to28Thevalueoflong-termincentivepayiscomputedbyHewitt.Stockoptions are valued using a modied version of the Black-Scholes modelthat takes into account vesting and termination provisions in addition tothestandardvariablesof interest rates, stockpricevolatility, anddivi-dends. As is standard practice among compensation consulting rms, theother components of long-term incentives are valued using an economicvaluationsimilar totheBlack-Scholesthat takesintoaccount vesting,termination provisions, and the probability of achieving performancegoals.29SeeWulf(2006)foradditionalanalysisoftherelationshipbetweendivisional manager incentives and organizational structure.TABLE 6.ORGANIZATIONAL SPANAND DEPTHFIRM FIXED-EFFECTS REGRESSIONSIndependent VariableSPAN DEPTH(i) (ii) (iii) (iv)log(Employees) 0.172 0.163 0.307*** 0.294***(0.234) (0.237) (0.081) (0.072)COO 0.964*** 0.457***(0.148) (0.039)CAO 0.344** 0.038(0.169) (0.043)1987 0.291** 0.264** 0.092** 0.085**(0.138) (0.133) (0.043) (0.039)1988 0.320* 0.216 0.053 0.011(0.170) (0.164) (0.053) (0.048)1989 0.569*** 0.462*** 0.143** 0.102*(0.172) (0.164) (0.058) (0.054)1990 0.544*** 0.432** 0.183*** 0.141**(0.178) (0.170) (0.063) (0.058)1991 0.462** 0.326* 0.215*** 0.152***(0.188) (0.178) (0.062) (0.057)1992 0.562*** 0.463** 0.139** 0.101*(0.194) (0.185) (0.065) (0.057)1993 0.661*** 0.530*** 0.167** 0.098(0.190) (0.182) (0.066) (0.060)1994 1.077*** 0.917*** 0.219*** 0.142**(0.207) (0.200) (0.067) (0.061)1995 1.407*** 1.242*** 0.231*** 0.146**(0.213) (0.207) (0.071) (0.066)1996 1.303*** 1.154*** 0.283*** 0.208***(0.223) (0.220) (0.069) (0.065)1997 1.776*** 1.644*** 0.270*** 0.193***(0.244) (0.240) (0.070) (0.065)1998 2.349*** 2.183*** 0.345*** 0.251***(0.272) (0.269) (0.079) (0.073)Constant 4.816*** 5.244*** 0.498* 0.266(0.695) (0.702) (0.253) (0.222)Observations 3264 3264 2381 2381Number of rms 369 369 323 323R-squared 0.49 0.52 0.65 0.71Dependent variables are SPAN (number of positions reporting to CEO) and DEPTH (rm average number of positions between the CEO and the divisional manager).Notes: Includes all rms in the sample that appear for at least two years. All specications include rm xed effects. All variables have been Winsorized at the 99th percentile. log(Employees) is dened as thelog of the number of employees in the rm. COO and CAO are dummy variables equal to 1 if the rm reports a chief operating ofcer and chief administrative ofcer, respectively. All specications report robuststandard errors by clustering at the rm level. ***/**/* represent signicance at the 1%/5%/10% level.THEFLATTENINGFIRM 769light monitoring and increased delegation of authority, as hedoesnothaveenoughtimefordetailedscrutinyofallhissubordinates. That authorityisbeingdelegatedcouldalsoexplain why long-term incentive pay is increasing for thosewho are moving closer to the top.The reader should not, however, conclude that atteningis simply decentralization of CEO authority. A broader spanof control alsosuggeststheCEOsdirect involvement indecisionsacrossagreaternumberoforganizational units.Let us now turn to possible explanations.IV. Possible Explanations for the Flattening of FirmsA. Increased Competition in Product MarketsOne set of possible explanations has to do with the morecompetitiveenvironmentinproductmarkets.Deregulationand increased trade has enhanced product market competi-tionoverthelast fewdecades. Not onlyhastherequiredspeed of response for rms increased, it has put a premiumon employee competence and creativity. The tall hierarchiesof the past may no longer be as effective.One reason may simply be because decisions need to betakenmorequicklytotakeadvantageofeetingopportu-nities in the marketplacethis is suggested by the GE CEOJeffrey Immelts desire, cited in the introduction, for fasterdecision making and execution. It takes time for eachmanagerial layer to give approval to a decision. As the speedincreaseswithwhichanaldecisionisneededtoavailofopportunities, either a number of opportunities are forgonewith the attendant loss of value, or nal decisions aredelegatedfurtherdownahierarchywithattendant lossoftop management control. Ceteris paribus, Williamson(1967) or CalvoandWellisz (1978) wouldsuggest thatorganizations would tend to become atter in this environ-ment.TABLE 7.DIVISIONAL MANAGER PAYAND DEPTH: OLSAND DIVISION FIXED-EFFECTS REGRESSIONSIndependentVariableDivisional ManagerSalary BonusDivisional ManagerLT IncentivesOLSDivisionFixed Effects OLSDivisionFixed Effects(i) (ii) (iii) (iv)log(Employees) 0.059*** 0.060* 0.046*** 0.084*(0.023) (0.032) (0.015) (0.047)log(Division Employees) 0.128*** 0.083*** 0.042*** 0.038***(0.013) (0.011) (0.008) (0.008)DDEPTH 0.141*** 0.065*** 0.059*** 0.053***(0.026) (0.012) (0.015) (0.012)1987 0.080*** 0.078*** 0.035* 0.022(0.016) (0.015) (0.019) (0.023)1988 0.162*** 0.139*** 0.046 0.016(0.023) (0.020) (0.029) (0.028)1989 0.182*** 0.175*** 0.058** 0.052*(0.024) (0.018) (0.028) (0.030)1990 0.205*** 0.202*** 0.118*** 0.115***(0.027) (0.022) (0.030) (0.030)1991 0.213*** 0.216*** 0.098*** 0.105***(0.026) (0.021) (0.027) (0.029)1992 0.279*** 0.281*** 0.104*** 0.108***(0.027) (0.022) (0.030) (0.031)1993 0.291*** 0.314*** 0.092*** 0.102***(0.029) (0.025) (0.026) (0.031)1994 0.414*** 0.402*** 0.166*** 0.160***(0.035) (0.026) (0.033) (0.039)1995 0.431*** 0.458*** 0.222*** 0.223***(0.039) (0.029) (0.037) (0.042)1996 0.429*** 0.464*** 0.266*** 0.304***(0.043) (0.033) (0.038) (0.044)1997 0.526*** 0.545*** 0.382*** 0.373***(0.048) (0.035) (0.045) (0.050)1998 0.531*** 0.539*** 0.362*** 0.351***(0.039) (0.037) (0.045) (0.056)Constant 11.236*** 11.427*** 0.061 0.164(0.087) (0.124) (0.061) (0.150)Observations 9915 9915 9915 9915R-squared 0.43 0.86 0.17 0.66Dependent variables are (log) divisional manager salary plus bonus and divisional manager LT incentives (ratio of value of long-term incentive pay to salary plus bonus).Notes: Includes all divisions in the sample that appear for at least two years. All variables have been winsorized at the 99th percentile. Divisional manager LT incentives is dened as the ratio of the value oflong-term incentive pay for divisional managers to the sum of the salary and bonus. Long-term incentive pay includes restricted stock, stock options, and other forms of long-term incentives (such as performanceunits, performance share plans, and phantom stock). Refer to footnote 27 in the text for the consulting rms valuation of long-term incentives. DDEPTH is dened as the number of positions between the CEOand the specic divisional manager position. log(Employees) is the log of the number of employees in the rm. log(Division Employees) is the log of the number of employees in the division. All specications reportrobust standard errors by clustering at the rm level. ***/**/* represent signicance at the 1%/5%/10% level.THEREVIEWOFECONOMICSANDSTATISTICS 770Also, greater competition may increase the complexity ofthe decisions that have to be made as well as the variety ofdata that impinge onthe decision. Tall hierarchies withintermediatemanagersmicromanagingtheworkofopera-tional managers may stie initiative (see, for example,Aghion & Tirole, 1997). Also, information may be hard toconvey up a hierarchy with the necessary detail and color,thus reducing managers incentive to collect it (Stein, 2002).Thustall hierarchiesmaybecomedysfunctional, withtopmanagers not having the information to make the rightdecisions and operational managers not having the incentiveto make them.Finally, as thedevelopment of nancial markets has in-creasedaccesstophysicalcapital,andashumancapitalbe-comes more important to a rms comparative advantage (see,for example, Dessein, 2002; Rajan & Zingales, 2000; Roberts&VandenSteen, 2000), tall hierarchies mayleadtotopmanagement losing the residual rights of control. In GrossmanandHart (1986), subordinatemanagersaresaidtobecon-trolledbyvirtueoftopmanagementsownership(actual ordelegated) of physical assets. If physical assets become rela-tivelyunimportant, ownershipbecomes less effective as ameans of organizational control. Tall hierarchies become lessviable. Instead, asRajanandZingales(2001)argueintheirdevelopment of the Grossman-Hart framework, top manage-ment has to build up control. It does this by establishing directcontact with lower-level managers (that is, attening the rm)and getting them to make human-capital-specic investmentsvis-a`-vis top management.30Thus the human-capital-intensivermisheldtogetherbyawebofhuman-capital-specicin-vestments, which are made possible by the atter hierarchy. Inaddition, employees get the promise of substantial ownershiprights, especially at the top, giving them an incentive to staywiththermdespitehavingmanycompetitorsfor thetoppositions.Tests of the broad hypothesis could be developed. Forinstance, using measures of the timing and extent of deregu-lation of different industries, we can check whether deregula-tion led to attening. Of course, it would be important to checkthatthederegulationwasnotanticipated.Similarly,onecanlook at import penetration as a measure of enhanced compe-tition.Apreliminaryanalysissuggeststhat thetrendofde-creaseindepthismorepronouncedinindustrieswherethepercentagechangeinimportswashigherbetweentheyears1990 and 1994, based on data documented in Feenstra (1996).However, more careful analysis that corrects for the endoge-neity of imports (imports are more likely in industries that arenot efcient), and that distinguishes between imports of nalgoods and imports of inputs, will be required for results to beconvincing. We leave such analysis to future work.B. Improvements in Corporate GovernanceAn important class of explanations has to do with agencycosts. In particular, a number of theorists have hypothesizedthat management, left to itself, might want to expand its turfand sense of worth (see, for example, Jensen, 1986; Jackall,1988; Osterman, 1996; Parkinson, 1958; Useem, 1996) byhiringlegionsofuselessmiddlemanagers. Thismayhavebeenpossible inthe past whenmanagement was inade-quately monitored. Equivalently, if the external governanceof the rm is poor, rms may not re incompetent manag-ers, but simply hire new ones to do their job.Ifrmsdevelopedtall, overstaffedhierarchiesbecauseofempire building, then improvements in corporate governancecouldexplainthetrendtowardatterorganizations. Gover-nancebenetedinthe1980sfromthewaveofhostiletake-overs, which stepped up pressure on the large rms thatconstituteoursample. Thecorporateraider, Carl Icahn, de-scribed his goal as eliminating layers of bureaucrats reportingtobureaucrats.31Inthe1990s, largeinstitutional investorsreplaced the hostile takeover as the source of governance (see,for example, Kaplan, 1996). Useem (1996) suggests that thegrowing dominance of institutional investors in the stockmarket has forced structural change in corporations: the elim-ination of layers of middle management and the restructuringof rms into more autonomous business units.However, when we regress the depth of a rms organiza-tional structure on crude proxies for the extent of governancepressure on the rm, such as the extent of institutional share-holding in that rm(lagged 1 year) or a measure of the strengthof outside governance compiled by Gompers, Ishii, and Met-rick(2003), wendlittlesystematicrelationship(estimatesavailablefromauthors). Moreover, if greater depthwereasymptom of empire building, it should hurt the rms value,and we should see a negative correlation between Depth andthe market-to-book ratio. In a regression of a rms market-to-book ratio on rm size, number of segments (diversied rmstypically have a lower market-to-book ratio), Depth, yeardummies, and xed effects for the rm, we nd no relationshipbetween the market-to-book ratio and Depth.Ofcourse, oneexplanationofthesendingsisthat themarket for corporate control worked perfectly. Some rmsmade timely changes in their organizational structure, whilethose that did not swiftly attracted external governancepressure, whichforcedthemtochange. As a result, wemight nd no relationship between organizational structureandmeasuresof governance. Similarly, becauseall rmsadjusted in a timely fashion to the optimal extent, whethervoluntarilyornot,theremightbenorelationshipbetweendepth and rm value. From all this, we can only conclude30The entire organization becomes atter in Rajan and Zingales(2001)senior managerscannot riskgivinglower managerstoomanysubordinates, lest they become too independent. Hierarchies becomewider, middlemanagersareeliminated, andthermbifurcatesintotopmanagement, who are owners/partners and can be trusted with commandover many subordinates, and worker/managers, who cannot be trusted tillthey have served time in the rm [see Rebitzer and Taylor (1997) for anearly study of the structure of law rms suggesting this pattern].31Quoted in Osterman (1996, p. 17).THEFLATTENINGFIRM 771that more work is needed to establish that better corporategovernance has led to atter hierarchies.C. Information TechnologyAnotherquiteplausibleexplanationfortheatteningofhierarchies is changes in information technology. In a clas-sicarticle, Leavitt andWhisler (1958) predictedthat theintroductionof informationtechnologyintoorganizationswould reduce the number of middle managers because theirinformation gathering and coordinating role would be elim-inated. Though there is some evidence that the introductionofinformationtechnologyleadstosmallerrms(see, forexample, Brynjolfsson et al., 1994), others have argued thatthe introductionof informationtechnologyincreases therichness of data to be analyzed and acted upon, and there-forecreatesmoreof arolefor middlemanagers[for anexcellent discussion, see Pinsonneault and Kraemer (1997)].As recent models suggest, theoretical predictions of theeffect of improvements in information technology on organi-zational changedependonwhether informationtechnologyreduces the cost of communication or whether it increases thecapabilityoflowermanagerstoaccessinformationtomakedecisions(seeGaricano, 2000). Accordingtohistheory, in-creases in the use of information technology increase the spanof control for managers, but the effect on the depth of hierar-chies is more ambiguous (predictions depend on whether thetechnology primarily eases communication or access to infor-mation). Thus a careful test of information-basedtheoriesrequires much more detailed knowledge of the kind of workdoneinaposition. Whencombinedwiththedifcultyofobtaininggoodproxiesontheextent ofuseofinformationtechnology, this leads us to think tests are again best left forfuture work.32V. ConclusionIn conclusion, we have unearthed a new set of facts aboutthe changing nature of corporate hierarchies: rms arebecomingatter, the CEOspanis broader, intermediatemanagers are being dispensed with, and divisional manag-ers are getting more authority, higher pay, and greaterincentive pay as they come closer to the CEO. Although ourndings suggest that corporate hierarchies are becomingatter, this phenomenon cannot be characterized simply ascentralization or decentralization. On the one hand, the CEOisgettingdirectlyconnecteddeeperdownintheorganiza-tion across a greater number of organizational units, a formofcentralization. Ontheotherhand, decision-makingau-thority and incentives are also being pushed further down, aform of decentralization. We have offered a set of explana-tionsforthesefacts. Testingtheseandotherexplanationsoffers ample scope for future work.Insum, then, thispaperunearthsinterestingpatternsofchange in rm hierarchies and provides some evidence thatthishastodowithchangesinthenatureoftheactivitiesbeing governed. 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The corporations second in com-mand, provided the persons span of responsibility is as broad oralmost as broad as the chief executives, and provided he or shehaslineratherthanstafforadvisoryresponsibility. Thispersonmay be the president if the chief executive ofcer is the chairmanof the board.3. Chiefadministrativeofcer(CAO). Functionalheadresponsiblefor the administration of two or more major, nonrelated corporatestaff functions such as nance, human resources, law, purchasing,dataprocessing, publicrelations, andlong-rangeplanningandbusiness development.4. Chief nancial ofcer (CFO). Functional head responsible for allnancial operations of the corporation. Has responsibility for boththe treasury and accounting functions. Indicate whether responsi-bilitiesalsoincludedataprocessing, investor relations, internalaudit, and taxes.5. Long-rangeplanning&businessdevelopment. Functional headresponsiblefor developingandobtainingagreement onoverallcorporate strategy to enhance sales and prots. Recommends theallocation of resources to existing businesses, acquisitions of newbusinesses, and disposition of existing businesses.6. General counsel. Theheadof all legal affairsof thecompany.Responsible for, or may be, corporate secretary; supervises outsidelegal counsel.7. Human resources. Head of all human resources with responsibilityfor establishing and implementing corporation-wide policies.8. Chief informationofcer(CIO). Thehighest level of operatingmanagementoverthecombinedfunctionsofprogramming,dataprocessing, machine operation, and systems work related to dataprocessing.9. Public relations. Functional head responsible for the developmentanddisseminationof favorablepersuasivematerial inorder topromote goodwill, develop credibility, and create a favorablepublic image for the company.10. Group chief executive (or group manager). The highest authorityin the group. A group is the highest level of multiple prot centerlinking the corporate CEO or COO directly to two or more singleprot center units (divisions).11. Division chief executive (or divisional manager). The highestauthorityinthedivision. A divisionisthelowestlevelofprotcenter responsibility for a business unit that engineers, manufac-tures, and sells its own products.FIGUREA1.EXAMPLE OF REPORTINGLEVELS, DEPTH, SPAN, ANDDESCRIPTIONS OF TYPES OF ORGANIZATIONAL UNITSTypes of organizational units: Acorporate unit is the highest management organization level of the parent company, responsiblefor its overall direction. A group is the highest-level multiple prot center linking the corporate chief executive ofcer orchief operating ofcer directly to two or more single prot center units (divisions). Adivisionis the lowest-level prot center responsibilityfor a business unit that engineers,manufactures, and sells its own products. A plant is a budget or cost center whose general manager supervises manufacturing, as well asservice functions, such as accounting, personnel, purchasing, and product engineering, but usuallyno R&D engineering. More important, the manager of a plant never has sales responsibility.THEFLATTENINGFIRM 773