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Whats My Style? The Influence ofTop Managers on Voluntary Corporate

Financial Disclosure

Linda Smith Bamber

The University of Georgia

John (Xuefeng) Jiang

Isabel Yanyan Wang

Michigan State University

ABSTRACT: Financial economics has posited a limited role for idiosyncratic noneco-

nomic manager-specific influences, but the strategic management literature suggests

such individual influences can affect corporate outcomes. We investigate whether indi-

vidual managers play an economically significant role in their firms voluntary financial

disclosure choices. Tracking managers across firms over time, we find top executives

exert unique and economically significant influence manager-specific fixed effectson

their firms voluntary disclosures, incremental to known economic determinants of dis-

closure, and firm- and time-specific effects. Managers unique disclosure styles are

associated with observable demographic characteristics of their personal backgrounds:

managers promoted from finance, accounting, and legal career tracks, managers born

before World War II, and those with military experience develop disclosure styles dis-

playing certain conservative characteristics; and managers from finance and account-ing and those with military experience favor more precise disclosure styles. These

plausible associations confirm that our estimated manager-specific fixed effects capture

systematic long-lived differences in managers unique disclosure styles.

Keywords: voluntary disclosure; management earnings forecasts; individual

differences; upper echelons theory.

Data Availability: Data are publicly available from the sources identified in the text.

We are grateful for constructive comments from participants in the 2008 Midwest Accounting Research Conference and the2008 Southeast Summer Accounting Research Colloquium, as well as workshop participants at the University of Con-necticut, Florida State University, Norwegian School of Economics and Business Administration, and the Turku School ofEconomics. Special thanks to Ben Ayers, Mark Bagnoli, Michael Bamber, Larry Brown, Daniel Feldman, Pat Hopkins,Steve Kachelmeier, Grace Pownall, K. Ramesh, Hannu Schadewitz, Jack Stecher, Wayne Thomas, Eric Yeung, two

anonymous reviewers, and especially Marilyn Johnson for detailed comments and in-depth discussions that helped usimprove this paper. Professor Bamber is grateful for financial support from the J.M. Tull School of Accounting and theTerry College of Business. Professors Jiang and Wang are grateful for financial support from the Department of Accountingand Information Systems at Michigan State University.

Editors note: Accepted by Wayne Thomas.

THE ACCOUNTING REVIEW American Accounting AssociationVol. 85, No. 4 DOI: 10.2308/accr.2010.85.4.11312010pp. 11311162

Submitted: August 2008Accepted: January 2010

Published Online: June 2010

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I. INTRODUCTION

W

e investigate two related research questions: 1 Do top managers exhibit unique andeconomically significant individual-specific styles in voluntary corporate financial dis-

closure?2 If so, are managers unique experiences, as evidenced by observable de-

mographic characteristics of their personal backgrounds, associated with cross-sectional differ-ences in their overall disclosure styles?

Published theoretical and archival research in economics, finance, and accounting has largely

posited a limited role for idiosyncratic noneconomic manager-specific influences in explaining

cross-sectional differences in corporate choices such as voluntary disclosure.1

Neoclassical eco-

nomic theory assumes individuals are rational optimizers, and is often characterized as providing

no role through which individuals could exert idiosyncratic influence on corporate outcomese.g.,Weintraub 2002; Bertrand and Schoar 2003. Agency theory proposes a less extreme, but stilllimited role through which individual managers could idiosyncratically influence corporate deci-

sions. In this perspective, managers respond rationally to: 1 the firms economic environment,and 2 the firms monitoring mechanisms and managers contractual incentives. As a result,research has typically focused on representative agents because individual managers can be

induced to make similar choices through appropriate monitoring and contractual incentives. In this

sense, neoclassical and agency theories allow little role for noneconomic manager-specific pref-

erences to affect corporate outcomes. Two streams of research in management lead to a similar

conclusion, reasoning that: 1 entrenched norms and cultures in large corporations constrainmanagers choices e.g., Lieberson and OConnor 1972, and 2 similarity in managers back-grounds and experiences rising through the corporate ranks further limits heterogeneity e.g.,Hittand Tyler 1991.

In contrast, Hambrick and Masons1984 upper echelons theory predicts that managers arenot effectively interchangeable. Their theory posits that idiosyncratic differences in managers

experiences are associated with differences in important personal values and cognitive styles such

as honesty and tolerance of ambiguity, which can lead managers to make different choices,

particularly in complex situations lacking clear and calculable solutions.Hambrick and Mason

1984 further argue that such preferences can in turn lead to different organizational outcomes.

Thus, we investigate whether individual top managers play a significant incremental role in ex-plaining cross-sectional variation in corporate voluntary disclosure choices, after controlling for

known economic determinants of disclosure and firm-specific effects. In other words, do man-agers exhibit economically significant individual-specific disclosure styles?

To address this question, we construct a panel data set that tracks top managers over the

period 19952005. Given that firms are associated with both the key independent variable man-agers and the dependent variablesfirms disclosure choices are sticky over time, it is critical tocontrol for firm-specific effects to avoid a correlated omitted variable problem, and to cleanly

isolate manager-specific effects. By isolating manager-specific fixed effects on firms disclosure

characteristics, after controlling for known economic determinants of disclosure, firm fixed effects,

and time period fixed effects, we can assess not only the existence, but also the magnitude, of

individual managers incremental effects on their firms voluntary disclosures. We refer to this

incrementalmanager-specific fixed effect as the managers style.

Our results suggest top managers exert economically significant individual-specific influenceover five aspects of management forecasts: forecast frequency, forecast precision, news conveyed

1Our study focuses on properties of one of the most important and widely investigated forms of voluntary financialdisclosuremanagement earnings forecaststhat Hirst et al. 2008, 315 characterize as one of the key voluntarydisclosure mechanisms by which managers establish or alter market earnings expectations, preempt litigation concerns,and influence their reputation for transparent and accurate reporting.

1132 Bamber, Jiang, and Wang

The Accounting Review July 2010American Accounting Association


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by the forecast, and the bias in and accuracy of the forecast. We assess the economic significance

of the manager-specific fixed effects along three dimensions. First, adding manager-specific fixed

effects to the base models that include the economic determinants, firm-specific effects, andtime-period specific effects increases explanatory power by 7.6 to 10.3 raw percentage points,translating to increases of 29.9 percent to over 400 percent relative to the base models adjusted

R2s. Second, manager-specific fixed effects are pervasive: between 38 percent and 51 percent of

the individual manager-specific fixed effects are significant at the 10 percent level, much greater

than expected by chance. Third, the distributions of managers fixed effects reveal economically

material differences. For example, replacing a manager at the 25th percentile of the distribution for

forecast frequency with one at the 75th percentile more than triples the number of forecasts.

Having established that individual managers exhibit significant idiosyncratic disclosure

stylescontrary to implicit assumptions of traditional financial economics researchour second

question is: How do managers personal experiences influence their own disclosure styles?

Upper echelons theory suggests that observable demographic characteristics of managers

backgrounds reflect key formative experiences that are associated with managers unique cognitive

styles and values. For example, this literature argues that managers functional career tracks e.g.,

marketing, accounting, legalaffect their preferencese.g.,Hambrick and Mason 1984;Jensen andZajac 2004. We find that, on average, managers promoted from legal backgrounds tend to guideexpectations down reflecting greater sensitivity to litigation risk and managers promoted fromaccounting and finance develop more precise disclosure styles that are conservative in underesti-

mating upcoming earnings. Consistent with evidence that individuals who experienced the after-

math of the Great Depression and associated stock market crash are more conservative e.g.,Malmendier and Nagel 2008;Zemke et al. 2000, we find that managers born before World War IIare more conservative in being reluctant to forecast. We also find that military experience leads

managers to develop styles favoring more precise forecasts that guide expectations down, consis-

tent with lower tolerance for ambiguity, conservatism, and valuing honesty and integrity over

self-intereste.g., Soeters 1997; Goertzel and Hengst 1971; Franke 2001. Finally, recent criticsassert that M.B.A. programs overemphasize the pursuit of self-interest e.g., Gintis and Khurana2008. We find that M.B.A.s tend to guide expectations upward, but their forecasts are moreaccurate. Coupled with our evidence on the magnitude and pervasiveness of the manager-specific

fixed effects, finding that managers unique disclosure styles exhibit plausible associations with

their distinctive permanent personal demographic characteristics confirms that we are capturing

systematic long-lived differences in managers unique styles and not just random noise.Our study makes several contributions. First, it responds to the Brochet et al. 2009, 32

suggestion that research may explore whether disclosure policies vary systematically with

managerial style. We provide evidence thatin contrast to the implicit assumption in most prior

financial economics researchthis hitherto unexplored personal style dimension plays a signifi-

cant incremental role in explaining cross-sectional differences in voluntary corporate financial

disclosure, even after controlling for economic determinants of disclosure and firm-specific andtime-period-specific fixed effects. Our evidence that not only CEOs, but also CFOs and GeneralCounsels, exhibit distinct disclosure styles responds toFinkelstein and Hambricks 1996call for

research on the influence of executives beyond the CEO level.Our second contribution is a response to the Hirst et al. 2008,316 call for a better under-

standing of the choices managers make once they decide to issue an earnings forecast e.g.,forecast precision, which Hirst et al. 2008 suggest is an important direction for both theorydevelopment and empirical research. Our study provides empirical evidence that managers de-

velop unique and economically significant styles concerning detailed attributes of voluntary dis-

closure, and these styles reflect their personal demographic characteristics such as functional

Whats My Style? The Influence of Top Managers on Voluntary Corporate Financial Disclosure 1133



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career track, age cohort, military experience, and education. Collectively, our evidence suggests

that exploring the roles individual managers play in other financial reporting choices is a fruitful

avenue for future research.

Third, we contribute more broadly to the nascent manager-effects literature. While Bertrand

and Schoar 2003 show that managers matter in core strategic operational and financing deci-sions, the magnitude of managers influence varies widely: effects are generally greater for high-

profile strategic decisions like acquisitions, and smaller for operational financing decisions like

cash holdings. Our evidence that managers not only matter, but matter significantly in seemingly

second-order decisions such as the details of firms voluntary disclosure decisions, extends the

range of corporate decisions in which idiosyncratic manager styles are known to play an economi-

cally significant role. More importantly, our study contributes beyond existing research by inte-

grating a broad set of literatures to provide conceptual bases for considering: 1 when and whymanagers mightor might notmatter, and 2 why and how characteristics of managers per-sonal backgrounds likely affect their idiosyncratic disclosure styles.

Finally, from a practical perspective, evidence that disclosures reflect manager-specific styles

suggests that initiatives intended to remedy disclosure problems such as upward-biased forecasts

e.g., stock hyping observed by Lang and Lundholm 2000 may be more effective if theytarget the individual manager, as the Sarbanes-Oxley Act does in holding managers responsible for

the firms financial reports.

II. CONTROVERSY OVER THE ROLE INDIVIDUAL MANAGERS PLAY IN

CORPORATE DECISIONS

Differing Perspectives on the Role Individual Top Managers Play in Corporate Decisions

Neoclassical economic theory is often characterized as allowing no role through which idio-

syncratic differences among individuals can affect corporate outcomes e.g.,Weintraub 2002. Forexample, in a neoclassical view of the firm top managers are homogeneous and selfless inputs

into the production process anddifferent managers are regarded as perfect substitutes for oneanotherBertrand and Schoar 2003,1173.Agency theoryallows individuals to differ in attributessuch as effort aversion, but typically focuses on representative agents because monitoring and

contractual incentives can induce individuals to make similar choices e.g., Christensen andFeltham 2003. Grounded in these traditions, archival research has typically abstracted from non-economic manager-specific effects on corporate choices.

2

Two streams of research in strategic management similarly conclude that managers are largely

interchangeable. First, the external control perspective suggests that environmental and organiza-

tional constraints such as entrenched norms and cultures limit managers choices e.g.,Liebersonand OConnor 1972;Hannan and Freeman 1977.Legitimacy constraints are particularly limiting,as managers conform to external expectations of rationality by imitating other managers, increas-

ing homogeneity e.g., Spender 1989; Hambrick et al. 1993; Chalmers and Godfrey 2004. Sec-ond, the socialization and selection processes top managers experience rising through the corpo-

rate ranks further limits heterogeneityHitt and Tyler 1991;Hambrick 2007, withDiMaggio andPowell1983, 152 asserting such mechanisms create a pool of almost interchangeable individu-als who occupy similar positions across a range of organizations and possess a similarity of

orientation and disposition. For example, most CEOs ofFortune1000 firms are white males with

college degrees, many from elite institutions Bhargava and Jespersen 1993; Datz 2000. A sig-

2A few studies examine how manager-specific economic incentives such as stock-based compensation and insider tradingaffect managers propensity to issue a management forecast e.g.,Noe 1999;Nagar et al. 2003;Cheng and Lo 2006. Incontrast, we focus on noneconomic manager-specific effects on attributes of management forecasts.




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nificant stream of empirical research in strategic management concludes that idiosyncratic influ-

ence of individual top managers is limited e.g., Lieberson and OConnor 1972; Salanick andPfeffer 1977;Hitt and Tyler 1991.

In contrast, Hambrick and Masons 1984 upper echelons theory suggests that individualmanagers matter. A recipient of the Academy of Management Reviews Frame-Breaking Innova-

tive Theory Award in 2006 Kilduff 2006, the study points out that simple inventory and creditpolicy decisions may have calculable solutions. But in complex ambiguous situations plagued by

multiple and often incompatible goals, managers operate within the bounds of rationality, and

within these bounds their choices can be influenced by their idiosyncratic experiences and values

Hambrick and Mason 1984;Finkelstein and Hambrick 1996;Hambrick 2007.Voluntary disclo-sure is such a complex, ambiguous situation requiring tradeoffs among multiple conflicting goals,

such as:1 protecting proprietary information that competitors could use against the firm versus2 mitigating litigation riske.g., Dye 1986; Evans and Sridhar 2002. Hambrick and Masons1984 theory spurred a stream of empirical research in management, much of which concludesthat managers affect firm choicese.g.,Smith and White 1987;Thomas et al. 1991;Tihanyi et al.2000; Naranjo-Gil and Hartmann 2006; Crossland and Hambrick 2007. However, this research

does not isolate manager effects after controlling for firm effects.3

If unmodeled firm characteris-tics affect corporate choices, then by confounding managers effects with firm effects, this litera-

ture likely overstates any manager effects.

Archival research in finance and economics is just starting to explore whether individual

managers impose idiosyncratic influence on corporate decisions. The seminal study in this genre,

Bertrand and Schoar 2003, develops an innovative design that disentangles the manager effectfrom the firm effect by tracking managers across firms over time. They find that managers develop

unique individual-specific styles in operational and financing decisions. Individual managers

incremental effects are generally greater for key strategic decisions like acquisitions, but smaller

for operational financing policies such as cash holdings. If managers have any idiosyncratic

influence on corporate decisions, then it is most likely to be on high-profile core strategic decisions

where top managers are most interested and actively involved.

Ex ante,it is unclear whether managers would exert economically significant idiosyncraticinfluence on their firms voluntary financial disclosure choices. Individual top managers effects on

voluntary disclosure hinge on: 1 the extent to which managers act as economic agents versusindividuals with distinct communication styles, and 2 the discretion managers enjoy over thestrategic choiceHambrick 2007. Top managers who act primarily as economic agents are likelymore interested in and involved in high-profile strategic operational and financing decisions e.g.,acquisitions, strategic marketing, production expansion, but are less interested in and less in-volved in seemingly secondary decisions about detailed attributes of management earnings fore-

casts. This suggests that top managers would have limited if any effect on the firms voluntarydisclosure choices. On the other hand, research in psychology concludes that humans develop

long-lived, individual-specific communication styles e.g., Pennebaker and King 1999. If topmanagers have distinct communication styles, such as valuing openness and transparency, then

this would likely affect the characteristics of the firms voluntary disclosures. With respect to

discretion, top managers can in principle exercise discretion over management earnings forecasts,but their discretion is limited by the ex postverifiability of the disclosures and stickiness of firms

disclosure policies over timeHealy et al. 1999;Lang 1999.

3The only exception we found that does control for firm fixed effects is Crossland and Hambricks 2007 study of thecross-cultural differences in the effect of CEOs on measures of firm performance e.g., return on assets.




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To summarize, certain theories and evidence suggest managers will have at most limited

effect on their firms voluntary disclosure choices, whereas other theories and evidence suggest the

opposite. It is therefore an empirical question whether top managers exert economically significant

individual-specific influence over their firms voluntary disclosures. Thus, we investigate whether

individual managers develop unique disclosure styles, paying special attention to the magnitude ofany such manager-specific effects.

4

What Demographic Characteristics of Managers Personal Backgrounds Might Influence

Their Disclosure Styles?

To the extent that managers backgrounds, socialization, and selection processes create similar

experiences and induce similar values and cognitive styles, the demographic characteristics of

their personal backgrounds are unlikely to explain any differences in their disclosure styles e.g.,DiMaggio and Powell 1983; Hitt and Tyler 1991; Hambrick 2007. On the other hand, upperechelons theory suggests cross-sectional differences in managers demographic characteristics,

such as their functional career track, age, and education, differentially shape managers values and

cognitive bases, which in turn can affect their managerial styles e.g.,Hambrick and Mason 1984;Hitt and Tyler 1991. We focus on the role of observable demographic characteristics of managersbackgrounds since upper echelons theory recommends that An emphasis on background charac-

teristics, rather than psychological dimensions, seems essentialHambrick and Mason 1984,196;see alsoHambrick 2007,335.

Whereas certain demographic background characteristics are observable and reliably measur-

able, top managers especially of large corporations are reluctant to submit to batteries of psy-chological tests, which are too general and detached from executive issues to be useful for

studying top managers Finkelstein and Hambrick 1996, 46. That is, psychological test instru-ments intended for the general population are not tailored to identify finer psychological traits that

might distinguish among successful professional executives. It is therefore not surprising that

research using psychological measures has not found significant effects. For example, Sorter et al.

1964 and Faircloth and Ricchiute 1981 find that personality characteristics do not explainaccountants preferred reporting alternatives. In contrast, Faircloth and Ricchiute 1981, 53 find

that objective personal demographic characteristics such as education do play a significant role,prompting them to recommend that additional research should pay more attention to the effects of

demographic information, which may in fact be more informative than many previously tested

variables such as personality characteristics.

To guide our exploration of the relation between managers demographic characteristics and

their unique disclosure styles, we conducted a comprehensive review of a broad set of literatures

ranging from strategic management, to career counseling, to sociology, to psychology, to military

science, and to business education. We searched for theories or evidence suggesting how demo-

4A recent working paper by Brochet et al.2009 investigates the effect of CEO or CFO turnover on the frequency andprecision of management forecasts. When a new CFO is appointed, on average firms that provided frequent guidancebefore the turnover experience a temporary decrease in the quantity and precision of management earnings forecasts.When such firms appoint a new CEO, the decline in the frequency of management forecasts tends to be longer-lived

documented up to two years, but there is no effect on forecast precision. Thus, Brochet et al. 2009 document theeffect of a managerial transition per se on the firms disclosure policy. Our study is fundamentally different. Rather thanfocusing on the short- or medium-term effects of a shock resulting from a managerial transition per se, we focus onwhether a given individual manager exhibits a persistent disclosure style measured over at least six years across multipleemployers.

Another working paper byGe et al.2009explores the effects of CFOs on choices that affect mandatory financialreporting. They conclude that CFOs exert manager-specific fixed effects on GAAP earnings-related choices indicative ofearnings management e.g., abnormal accruals. They do not explore the effects of individual managers on voluntarymanagement earnings forecasts, which is the focus of our study.




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graphic characteristics highlighted inHambrick and Masons 1984 upper echelons theory mightplausibly be associated with cross-sectional differences in managers unique disclosure styles. Our

review suggests four demographic characteristics of managers personal backgroundsfunctional

career track, age cohort, other career experience specifically, military experience, and M.B.A.educationlikely influence managers unique disclosure styles.5

Functional Career Track

Hambrick and Masons 1984, 200 upper echelons theory suggests a managers primaryfunctional career track affects his/her choices because career experiences partially shape the

lenses through which they view current strategic opportunities and problems. Socialized in their

functional areas mindset, managers tend to converge on solutions to common business problems

Finkelstein and Hambrick 1996, 93. Empirical research confirms that managers pursue strategiesin line with their own functional expertise e.g., Smith and White 1987; Thomas et al. 1991;Jensen and Zajac 2004. Prior research characterizes individuals in technical financial functions asconventional, orderly, and inhibited Holland 1973; 1997, suggesting they may adopt conserva-tive disclosure styles.We consider fewer forecasts, downward guidance, or guidance that under-

shoots upcoming earnings as various dimensions of a conservative disclosure style. Managersfrom technical functions are also less tolerant of ambiguity Holland 1966;1997, 27, andHam-brick and Mason1984 posit that managers from finance favor more budget detail and thorough-ness, which suggests managers from finance or accounting may develop more precise communi-

cation styles. Executives with legal backgrounds are more sensitive to litigation risk, and so likely

favor communication styles that do not promise too much.6

Age Cohort

Upper echelons theory suggests that the managers age cohort can affect his/her values,

cognitive styles, and thus his/her decisions Hambrick and Mason 1984. Schuman and Scott1989show that the events an age cohort individuals born in the same eraexperiences during itsyouth affect later attitudes.Zemke et al.2000 classify managers born before World War II as an

important cohort, shaped by the lingering sacrifices and shortages of the Great Depression, theDust Bowl that wiped out the Great Plains farms, and the war years, all of which inculcated

conservative values. Emerging research in financial economics finds that cohorts who experienced

lower stock returns during their investing lives are more conservative Malmendier and Nagel2008.Blanchard1993 ascribes the decline in the equity risk premium to receding memories ofthe crash and the Great Depression, andPalsson 1996 finds that age is associated with greaterrisk aversion in portfolio holdings. Finally, Bertrand and Schoar 2003 find that managers fromolder birth cohorts choose lower levels of corporate expenditures, lower leverage, and larger cash

holdings, consistent with conservatism. These arguments suggest executives born before World

War II may develop more conservative communication styles, such as being less likely to issue

forward-looking statements for fear such disclosures may prove inaccurate, ex post.

5Upper echelons theory suggests that certain demographic characteristics affect managers cognitive styles and values,but we had to search elsewhere to support how these characteristics might plausibly affect managersdisclosure styles.As a result of this search, we explored two additional demographic characteristics beyond upper echelons theory: genderand whether the manager is from the firms founding family. Unfortunately, members of founding families of S&P 1500firms do not move to similar positions at other S&P 1500 firms. Consistent with the literature documenting thehomogeneity of managers backgrounds, our sample includes only six female managers.

6Bagley 2008, 379 argues that legally astute top managers make different choices because they appreciate theimportance of meeting societys expectations of appropriate behavior and of treating stockholders fairly.




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Military Experience

Upper echelons theory suggests that an executives other career experiences can affect his/her

decisions. We posit that military service is a different form of career experience that likely affects

a managers disclosure style. Military personnel tend to be less tolerant of ambiguity/uncertainty

e.g.,Goertzel and Hengst 1971;Soeters 1997, suggesting they may favor more precise commu-nication styles. A common theme is service before self Franke 2001, as the Army describesmilitary values as duty, selfless service, courage, integrity and a sense of justiceHeadquar-ters, Department of the Army 1993, 12. Individuals choosing military service tend to be con-servativee.g.,Goertzel and Hengst 1971;Franke 2001. They are likely to agree that honesty isthe best policy, that one should take action only when one is sure it is morally right, and are

less likely to believe it is acceptable to cut corners Franke 1998;2001. They place relativelylower value on income and promotion opportunitiesSoeters 1997. Such values suggest managerswith military experience may favor styles that tend toward prompt and unbiased disclosure of

unfavorable informationi.e., honesty about bad news.

M.B.A. Education

Upper echelons theory predicts managers holding M.B.A. degrees develop different styles

than those without such educational backgrounds. Finkelstein and Hambrick1996, 104 suggestM.B.A.s are part of the social and business elite who value conformity and conventionality.

M.B.A.s are also likely aware of the penalties the market exacts when firms fail to meet their own

earnings forecasts Chen 2004. These arguments suggest that M.B.A.s may adopt more conser-vative disclosure styles. On the other hand, post-Enron era critics have asserted M.B.A. programs

overemphasize neoclassical economics, where rational managers pursue their own self-interest

e.g., Ghoshal 2005; Gintis and Khurana 2008.7 Self-reported cheating levels are higher inM.B.A. than other graduate programs McCabe et al. 2006, and individuals who behave dishon-estly as students are more likely to behave dishonestly in the workplaceNonis and Swift 2001,suggesting M.B.A.s might be more likely to issue disclosures that spin the firms outlook.

III. RESEARCH DESIGN

The Existence and Magnitude of Individual Top Managers Voluntary Disclosure Styles

Sample and Data

Firms disclosure choices are sticky over time Healy et al. 1999;Lang 1999, but asHirst etal. 2008 point out, empirical models leave most of the cross-sectional variation in voluntarydisclosure choices unexplained. This suggests that unidentified firm characteristics likely affect

firms disclosure choices. Because firms are associated with both the key independent variable

managers and the dependent variables disclosure choices, it is necessary to control for firm-specific fixed effects to avoid misattributing firm effects to managers.

We therefore use a research design with strong controls for firm effects. We adopt Bertrand

and Schoars2003longitudinal design that tracks managers over time, and requires managers towork for two or more employing firms, with at least three years at each employer so the manager

has time to imprint his/her style. If the manager works at only one firm, then his/her effect isconfounded with the firm effect and it is not possible to cleanly separate the manager effect from

the firm effect. Figure 1 illustrates this design for two firms. For each firm, we control forfirm-specific fixed effects measured over the entire sample period. To isolate the effect of an

7Bertrand and Schoar 2003 provide some evidence that managers with M.B.A.s make more aggressive resourceallocation decisions. Because M.B.A. education focuses on operational and financing decisions and less on disclosure,evidence that an M.B.A. degree is associated with manager-specific effects on operating and financing decisions doesnot necessarily imply that there will be similar effects on managers voluntary disclosure decisions.




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individual manager on disclosureincremental to the effects of the firmswe measure the effect

of Manager A across the two employing firms, after controlling for Firm 1s fixed effect, Firm 2s

fixed effect, year fixed effects, and well-documented economic determinants of voluntary

disclosure.8

Manager As style is measured by his/her fixed effect.

Manager As fixed effect reflects how Firm 1s forecast attributes in period 1 deviate from

Firm 1s average forecast attributes, and how Firm 2s forecast attributes in period 2 deviate from

Firm 2s average forecast attributes after also abstracting from the effects of known economicdeterminants and year-specific effects. Thus, our estimated manager-specific fixed effects capturethe incremental effects of a manager at multiple employers, after controlling for any firm-specific

effects, over six or more years. This method also reduces concerns about correlated omittedvariables, which to explain our results would have to vary over time and across firms in the same

pattern as the movement over time and across firms of managers with unique disclosure styles.

From Execucomp, we record the five highest-paid managers for S&P 1500 firms. Our sample

period starts in 1995 when First Calls Company Issued Guideline CIG database became a morecomplete source of management forecasts Anilowski et al. 2007.9 From 1995 to 2005, weidentify 303 top managers that work for at least two different firms and stay employed by each

firm for at least three years. We focus on managers whose last position is CEO, CFO, or General

Counsel because these positions are more likely to influence voluntary disclosure. We match each

firm-year with management forecasts reported in CIG.

Model and Variable Definitions

We investigate five attributes of management earnings forecasts: frequency, precision, news,

direction of bias relative to actual earnings, and accuracy. The frequency of managers forecasts

F_Freq is the number of earnings-related forecasts the firm issues during the year which is 0 if

8FollowingBertrand and Schoar 2003,we retain all firm-years with data only in the estimation of the firm fixed effectsi.e., including Manager B observations for estimation of Firm 1s fixed effect and Manager C observations for estima-tion of Firm 2s fixed effect.

9Ajinkya et al. 2005, 350 conclude that CIG is a comprehensive source of management forecast information, afterperforming two small-sample tests in 1997 and in 2000 matching CIG forecasts with those identified in a keywordsearch of Factivaformerly the Dow Jones News Retrieval Service. Choi and Ziebart 2004 report similar results forthe period 19931996.

FIGURE 1

Research Design for Two Illustrative Firms

FIRM 1 FIRM 2

Period 1

(at least 3 consecutive years) Manager A Manager C

Period 2

(at least 3 consecutive years) Manager B Manager A

Manager As fixed effect is measured over Firms 1 and 2, after controlling for: (1) the fixed effect of Firm 1

(estimated over theentire sample period), (2) thefixed effect of Firm 2 (estimated over theentire sample period),

(3) fixed effects for each year, and (4) all of the time-varying economic determinants of disclosure.




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the firm issues no forecasts.10 We code forecast precision F_Precision as 3, 2, 1, and 0, forpoint, range, open-ended, and general impression forecasts e.g., Bamber and Cheon 1998; Ba-ginski et al. 2002.11 We measure forecast news as the difference between the forecast EPS ormidpoint of the range forecastand the prevailing median analyst forecast, scaled by lagged stock

priceF_Goodnews. We measure forecast bias F_BiasUP by comparing the management EPSforecast using point forecasts and the midpoint of range forecasts to ex postrealized EPS.12

Forecasts that exceed actual EPS are coded as 1 i.e., optimistic forecasts, those that equalactual EPS are coded as 0, and those that fall short of actual EPS are coded as 1i.e., pessimisticforecasts.13 Finally, we measure the inverse of forecast accuracy F_AbsError as the absolutevalue of the difference between the management EPS forecast using point forecasts and themidpoint of range forecastsand actual EPS, scaled by lagged stock price, followingAjinkya et al.2005.Exhibit 1 summarizes our variable definitions.

To test whether individual managers play unique, individual-specific roles in firms voluntary

financial disclosure, we estimate the following models:

Yit=+Xit+t+i+ it; 1

Yit=+Xit+ Managers +t+i+ it; 2

Yit=+Xit+ CEOs +t+i+ it; 3

Yit=+Xit+ CFOs +t+i+ it; 4

Yit=+Xit+ Counsels +t+i+ it. 5

Our unit of analysis is a firm-year. Yit is the management forecast attribute for firm i in year

t. When firms issue multiple forecasts in a year, we use firm-year averages for precision, news,

bias, and accuracy.14

The vector Xcontrols for a comprehensive set of economic determinants of

voluntary disclosure documented in prior literature, as summarized in Figure 2and explained in

the Appendix. Managers, our main variables of interest, are estimated coefficients for indicator

variables corresponding to each individual manager, and thus represent the individual managers

fixed

10F_Freq is skewed, but our inferences are robust if we redefine F_Freq as the natural log of 1 plus the number offorecasts. Our inferences are also robust when we conduct the analysis using a fixed effect count modelPoisson model,perCameron and Trivedi 2005.

11Our main analysis includes forecasts of all specificity levels. However, we obtain similar inferences using an alternativeinversemeasure of specificity where we code point forecasts as zero and range forecasts as the magnitude of the range,scaled by lagged share price.

12 We compare management earnings forecasts listed on First Call to actual earnings as reported by First Call to ensureconsistency, followingAjinkya et al. 2005.

13Our main analysis focuses on the direction of the bias, because the forecast error variable captures the distance of theforecast from ex postactual EPS. Nonetheless, we obtain similar inferences if we define F_BiasUP as the differencebetween the management forecast and ex postactual EPS, scaled by lagged share price.

14We conduct our analysis at the firm-year level because our goal is to assess the extent to which individual managersaffect overall firm disclosure policy. Untabulated sensitivity tests reveal that our results continue to hold if we use thelast forecast issued in a year. Any dependence among multiple observations from the same firm does not affect ourconclusions, because they continue to hold when we allow clustering of the error term at the firm level.




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EXHIBIT 1

Variable DefinitionsDependent Variables

F_Freqit number of management earnings forecasts firmi issued in year t;

F_Precisionit average precision of management earnings forecasts firmi issued in year t, wherepoint forecasts are coded as 3, range forecasts are coded as 2, open-ended forecastsare coded as 1, and qualitative forecasts are coded as 0;

F_Goodnewsit average news conveyed by forecasts firmi issued in year t, measured as the differencebetween the forecast EPS or midpoint of the range forecast and the prevailingmedian analyst forecast, scaled by lagged stock price;

F_BiasUPit average bias relative to ex postactual earnings in forecasts firm i issued in year t.a

Forecasts that exceed actual earnings are coded as 1, forecasts that equal actualearnings are coded as 0, and forecasts that fall short of actual earnings are coded as1for range forecasts, we code this variable based on the midpoint of the range ;and

F_AbsErrorit inverse of forecast accuracy, measured as the average absolute error in the forecaststhat firm i issued in year t, relative to ex postactual earnings. Specifically, we use theabsolute value of the difference between the management forecast using point

forecasts and the midpoint of the range forecasts and actual EPS, scaled by laggedstock price, multiplied by 100 to yield an error in percentage terms.

Control Variables

EPSit absolute value of the change in firm is earnings per share from year t1 to t,deflated by stock price at the end of year t1;

Dispit standard deviation of analysts forecasts of firm is year tearnings, divided by theabsolute value of the median forecast;

EPS_UPit indicator variable coded as 1 if firm is EPS in year tis greater than or equal to itsEPS in year t1, and 0 otherwise;

Lossit indicator variable that equals l if firm i reports a loss in year tCompustat item 172,net income, and 0 otherwise;

R&Dit firm is expenditures on research and development in year t, scaled by its total assets;

MktBkit market value of firm is common equity divided by the book value of its commonequity, at the end of year t;

Outside_Dirit

percentage of members of firmis board of directors during year t, who are not alsoofficers of the firm, from the Investor Responsibility Research Center IRRC;

%Instit percentage of firm is common stock held by institutions in year t, from ThomsonFinancial;

Lsizeit natural log of the market value of firmis common equity in year t;

#Analystsit number of analysts providing earnings forecasts for firm i in year t;

Litigationit coded as 1 if the firm is a member of one of the following high-litigation-riskindustries: SIC codes 28332836biotechnology, 35703577 and 73707374computers, 36003674electronics, 52005961retailing, and 87318734R&Dservice, and suffers a 20 percent or greater decrease in earnings; and 0 otherwise;

ClassActionit 1 if the firm is involved in a securities lawsuit in yeart, per the Stanford SecurityClass Action Clearinghouse;

Restructuringit 1 if the firm was engaged in a restructuring during year t;

Restatementit 1 if the firm had a restatement in yeart, per the General Accounting OfficesAccounting Restatement database;

Acquisitionit 1 if the firm has a merger or acquisition in yeart, per footnote 1 in the annualCompustat file; and

F_Horizonit number of days between the forecast date and the end of the fiscal period of theforecasted earnings number. We scale this forecast horizon by 360 for annualforecasts or by 90 for quarterly forecasts, so the variable measures the proportionof the fiscal period remaining at the date firm i issues the forecast.

(continued on next page)




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effects. t controls for year-specific fixed effects, and i controls for firm-specific fixed effects.15

15We estimate models 15 using a firm fixed effect model XTREG in STATA that estimates coefficients for theeconomic determinants, manager indicator variables, and year indicator variables. The estimation eliminates the unob-served time-invariant firm characteristics in models 15 i.e., the i by a within-transformation that demeans eachvariable for each firmWooldridge 2002,267. An alternative is OLS estimation with explicit firm indicator variables.That approach generates the same coefficient estimates on the economic determinants the vector X and the managerManagersand time period effects t, but it is computationally intensive, infeasible for models with thousands of firmsas is the case in one of our sensitivity tests , and it also generates higher adjusted R2. So our reported adjusted R2s aremore conservative.

EXHIBIT 1 (continued)

Additional Firm Characteristics

Mveit market value of firm is common equity at the end of year t, in millions;

Salesit sales revenue of firm i in year t, in millions;ROAit firm is net income in year tdivided by lagged total assets;

Levit firm is long-term debtCompustat item 9 item 34 divided by long-term debt plusthe book value of common equity Compustat item 60; and

Betait firm is equity beta for the fiscal period, calculated using daily equity returns and asingle factor CAPM.

Manager Demographic Characteristics

Acct/Fin 1 if managers rise from accounting/finance backgrounds, and 0 otherwise;

Legal 1 if managers rise from legal backgrounds, and 0 otherwise;

PreWWII 1 if managers were born before World War II, and 0 otherwise;

Military 1 if managers have military experience, and 0 otherwise; and

MBA 1 if managers hold an M.B.A. degree, and 0 otherwise.

a All actual EPS numbers are before extraordinary items.

FIGURE 2

Detailed Model Specification

Dependent Variable

(Yit) Vector of Control Variables (Xit)

Number of forecasts(F_Freqit)

|EPSit|, Dispit, EPS_UPit, Lossit, R&Dit, Mkt-Bkit,Outside_Dirit, %Instit, LSizeit,#Analystsit, Litigationit ,ClassActionit, Restructuringit, Restatementit, Acquisitionit

Forecast precision(F_ Precisionit)

Forecast news(F_ Goodnewsit)

Forecast bias

(F_ BiasUPit)

Forecast accuracy(F_ AbsErrorit)

|EPSit|, Dispit, EPS_UPit, Lossit, R&Dit, Mkt-Bkit,Outside_Dirit, %Instit, LSizeit,#Analystsit, Litigationit,

ClassActionit, Restructuringit, Restatementit, Acquisitionit,F_Horizonit




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Model 1 includes known economic determinants of voluntary disclosure choices as well as

time- and firm-specific fixed effects. Model 2 adds the manager-specific fixed effects. This enables

us to investigate not only the existence of, but also the magnitude of, individual managers

incrementaleffects on their firms voluntary disclosures after controlling for the known economic

determinants, as well as time- and firm-specific fixed effects. Models 3, 4, and 5 test for effects ofCEOs, CFOs, and General Counsels, respectively.

Testing Whether Demographic Characteristics of Top Managers Personal Backgrounds Are

Associated with Their Unique Disclosure Styles

Data, Model, and Variable Definitions

We hand-collect demographic characteristics of managers backgrounds from Marquis Whos

Who, Zoominfo, Mergent Online, Hoovers, NNBD.com, and company websites. To test whether

these characteristics contribute to managers individual disclosure styles, we regress the fixed-

effect coefficient estimates from Model 2after controlling for economic determinants, time- andfirm-specific fixed effects, on managers personal demographic characteristics:

m,Yi =0+1Acct/Fin +2Legal +3PreWWII+4Military+5MBA + . 6

m,Yi are the manager-specific fixed effects estimated in Model 2, where m represents the manager

and Yrepresents the disclosure attribute. Acct/Fin distinguishes managers rising fromaccounting

or finance backgrounds, and Legal distinguishes managers with legal backgrounds.16

Following

Zemke et al. 2000, we classify managers into two age cohortsmanagers born before WorldWar II PreWWII) versus those born after World War II.17 Military indicates the manager hasmilitary experience, and MBAindicates the manager earned an M.B.A. degree.

IV. RESULTS

Descriptive Statistics

Table1compares our sample firm-years to the population with at least three consecutive years

of data in Execucomp that also have at least one analyst following the firm, as reported by First

Call. Our sample firms tend to be larger, because managers of larger firms are more likely to move

to another firm in the S&P 1500 population covered by Execucomp. This biases againstfinding amanager-specific effect, because managerial discretionand, hence, any manager-specific

effectdeclines with company sizeFinkelstein and Hambrick 1996;Bertrand and Schoar 2003.Our sample firms are more levered, but similar in profitability and riskbeta.

On average, our sample firms issue 1.77 forecasts each year, slightly more than the population

average of 1.48p 0.05. Our sample firms forecasts are less biased relative to ex postactualearningsthan those of the population p 0.05. However, forecasts issued by our sample and thepopulation exhibit similar precision, newsrelative to prevailing analysts forecasts, and accuracy.The average forecast gives a range of values, guides expectations downward, and is downward-

biased relative to actual earnings.

Turning to the economic determinants, our sample firms are slightly less likely to enjoy an

increase in earnings during the forecast year, and have a larger proportion of outside directors,

16We expect the accounting/finance and legal career tracks to be most relevant to voluntary earnings-related disclosurechoice. Separate analysis of executives promoted from production and marketing tracks does not affect our inferences,nor were the coefficients on the marketing or production career track variables significant.

17Zemke et al. 2000 identify those born before 1943 as the Veterans cohort, those born between 1943 to 1960 as the

Baby Boomers, and those born between 1960 to 1980 as Generation Xers. Those born from 1943 to 1946 are oftenreferred to as the Sandwichgeneration, butZemke et al.2000consider them part of the Baby Boomerscultural cohort.We combine the Baby Boomers and Generation Xers because our sample includes only a handful of Generation Xers,and separating them does not yield any additional insights.




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higher institutional ownership, and larger analyst following. Our sample firms also have slightly

higher incidences of class action lawsuits, restructurings, and restatements, and their managementearnings forecasts have somewhat longer horizon. However, the sample and population exhibit

similar absolute changes in EPS, dispersion in analysts forecasts, incidence of losses, R&D

intensity, market-to-book ratios, litigation risk, and acquisition activity. In sum, our sample firms

are somewhat larger than the population, and exhibit other differences associated with larger firms,

but our sample does not differ on other fundamental economic characteristics such as riskbeta,return on assets, absolute changes in EPS, and market-to-book ratios.

TABLE 1

Comparison of Sample to the Population in the Intersection of Execucomp and First Calla

Variable

Sample Firms Execucomp/First Call Population

n Mean Std. Dev. Median n Mean Std. Dev. Median

Firm Characteristics

Mve* 3,920 11,066 30,774 2,592 18,987 6,349 21,305 1,282Sales* 3,920 7,847 19,578 2,217 18,987 4,281 12,474 1,058

ROA 3,920 0.04 0.16 0.04 18,987 0.04 0.37 0.05

Lev* 3,909 0.40 0.51 0.40 18,915 0.35 0.98 0.35Beta 3,915 0.98 0.56 0.87 18,937 0.97 0.56 0.87

Management Forecast Characteristics

F_Freq* 3,920 1.77 2.27 1 18,987 1.48 2.11 0F_Precision 2,169 1.97 0.72 2 9,321 1.96 0.73 2

F_Goodnews 1,920 0.16 0.58 0.04 8,193 0.18 0.69 0.05

F_BiasUP* 1,914 0.12 0.80 0.11 8,151 0.20 0.79 0.33F_AbsError 1,914 0.58 1.15 0.21 8,151 0.55 1.04 0.20

Economic Explanatory Variables|EPS| 3,920 0.07 0.15 0.02 18,987 0.06 0.14 0.02

Disp 3,920 0.11 0.28 0.03 18,360 0.10 0.26 0.03

EPS_UP* 3,920 0.63 0.48 1 18,987 0.65 0.48 1Loss 3,920 0.18 0.39 0 18,987 0.17 0.37 0

R&D 3,920 0.03 0.05 0 18,987 0.03 0.06 0

Mkt-Bk 3,920 3.30 3.58 2.34 18,987 3.22 3.35 2.30

Outside_Dir* 3,920 70.39 16.47 75 18,888 66.07 18.33 69.23%Inst* 3,920 63.61 18.99 65.58 18,961 61.34 20.81 63.07

LSize* 3,920 7.92 1.60 7.86 18,987 7.30 1.57 7.16#Analysts* 3,920 14.71 8.94 13 18,987 11.46 8 9

Litigation 3,920 0.10 0.30 0 18,987 0.10 0.30 0

ClassAction* 3,920 0.04 0.20 0 18,987 0.03 0.17 0Restructuring* 3,920 0.35 0.48 0 18,987 0.28 0.45 0

Restatement* 3,920 0.05 0.21 0 18,987 0.03 0.18 0Acquisition 3,920 0.21 0.41 0 18,987 0.21 0.40 0

F_Horizon* 2,169 0.44 0.31 0.47 9,321 0.42 0.33 0.45

*Indicates that our sample and the Execucomp/First Call population differ significantly both on t-tests and nonparametricWilcoxon rank sum tests p 0.05.a

We compare our sample firms to the population of firms with at least three consecutive years of data in Execucomp, andwith at least one analyst following from First Call.

Exhibit 1 defines all variables.




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The Existence and Magnitude of Individual Top Managers Voluntary Disclosure Styles

Main Results

The results of the manager fixed-effects analyses appear in Tables26.The primary inference

is that top managers have statistically andeconomically significant fixed effects on their firms

voluntary disclosure choices. We discuss these results in more detail.

Table2 presents the results for the frequency of forecasts. The F-tests from Model 2 indicate

TABLE 2

Testing Individual Top Managers Fixed Effects on the Number of Management Earnings

Forecasts

F_Freq(n 3,920)

a

EconomicDeterminants,

Year- andFirm-SpecificFixed Effects

(Model 1)

EconomicDeterminantsandManagerFixed Effects,


(Model 2)

EconomicDeterminantsandCEOs

Fixed Effects,


(Model 3)

EconomicDeterminants

andCFOsFixed Effects,


(Model 4)

EconomicDeterminantsandGeneral

Counsels FixedEffects, Year-

and Firm-Specific Fixed

Effects(Model 5)

Testing Economic Determinants 0

F-statistics 6.77 4.32 5.16 5.38 7.11

p-value 0.001 0.001 0.001 0.001 0.001Constraints 15 15 15 15 15

Testing Manager Fixed Effects 0

F-statistics 7.46 7.10 5.92 5.01

p-value 0.001 0.001 0.001 0.001Constraints 292 177 93 22

Adjusted R2 33.5% 43.5% 40.2% 36.4% 34.0%

Improvement in Adjusted R2 Relative to Model1:In Raw Percentage Points 10.0 6.7 2.9 0.5

As a % of Model 1s R 2 29.9% 20.0% 8.7% 1.5%

Distribution of Manager Fixed Effectsb

(n 292 Managers)

ManagerFixed Effect

% Significant at 10% Level 51%

Mean Effect 0.00

Median Effect 0.01

25th Percentile 0.97


Difference between 75th and25th Percentile

1.93

aWe report the results of five regressions after controlling for economic determinants, and year- and firm-specific fixedeffects. We control for heteroscedasticity using Whites standard errors. The adjusted R 2 is calculated based on theWithin R2 from XTREG, FE in STATA. Exhibit 1 defines the economic determinants.

bThe manager fixed effects are the estimated coefficients from Model 2 that controls for economic determinants as wellas year- and firm-specific fixed effects in estimating the incremental manager fixed effects.




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that the manager-specific fixed effects are jointly different from zero, after controlling for eco-

nomic determinants as well as firm- and time-specific fixed effectsp 0.001. We next assess theeconomic significance of these manager-specific fixed effects in three ways. We show: 1 theincrease in adjusted R2 from adding the manager fixed effects, both in terms of raw percentage

points, and in percentage changesi.e., the increase in adjusted R2 as a percentage of the adjustedR2 from Model 1,2 that the proportion of statistically significant manager fixed effects is muchhigher than expected by chance, and 3 that the interquartile range indicates meaningful cross-sectional differences in managers disclosure styles.

First, even after controlling for known economic determinants of disclosure as well as time-and firm-specific fixed effects, adding manager fixed effects to the base Model 1 significantlyimproves explanatory power. Adjusted R2 increases from 33.5 percent in the base model to 43.5

percent, an increase of ten percentage points in absolute terms and 29.9 percent 10/33.5 inrelative terms.

18Models 3 to 5 show how managers in the CEO, CFO, and General Counsel

positions contribute to the increase in explanatory power observed in Model 2.19

The second chart in Table 2 displays the two additional indicators of the economic signifi-

cance of the manager-specific fixed effects estimated in Model 2. Even after controlling for

economic determinants, 51 percent of the individual manager-specific effects are significant at the10 percent level, much higher than expected by chance. The interquartile range shows that replac-

ing a manager at the 25th percentile with one at the 75th percentile increases the number of

forecasts issued each year by 1.93, which is material given that the mean number of forecasts our

sample firms issue each year is 1.77Table1. Clearly, individual managers unique fixed effectsplay an economically significant role in firms forecasting frequency.

Tables 36 show that the economic determinants explain much less of the cross-sectional

variation in forecast precision, news, bias, and error 1.8 percent to 12.5 percent than of forecastfrequency33.5 percent, Table2, consistent with theHirst et al.2008observation that we knowless about the attributes of management forecasts than we do about the decision to issue a forecast.

For forecast precision, adding the manager-specific effects to the base Model 1 increases adjusted

R2 from 1.8 percent to 10.0 percent, an increase of 8.2 percentage points in absolute terms or anincrease of 456 percent in relative terms. Similarly, adding the manager-specific fixed effects tothe forecast news, bias, and error models increases adjusted R 2 by 9.5, 7.6, and 10.3 percentage

pointswhich translate to increases of 82 percent, 61 percent, and 82 percent in relative terms,relative to Model 1. The increases in adjusted R2 observed in Models 3 to 5 suggest that CEOs

and CFOs styles play a significant role in these forecast attributes, but the General Counsels role

is not economically meaningful except for the forecast error attribute.

The second chart in Tables 36 displays the distribution of manager-specific fixed effects

estimated in Model 2. Between 38 percent and 46 percent of the individual manager fixed effects

are significant at the 10 percent level, much higher than expected by chance. The interquartile

ranges further support the materiality of the individual manager effects. Table 3 shows that re-

placing a manager at the 25th percentile with one at the 75th percentile increases average precision

by 0.75, which is material relative to the unconditional mean of 1.97 per Table 1. Turning to

18The increase in adjusted R2 from adding manager-specific fixed effects compares favorably with the increase in adjustedR2 from adding manager-specific fixed effects to models of other corporate decisions. For example,Bertrand and Schoar2003find that adding manager-specific fixed effects to models of investment and financial policies increases adjustedR2 by an average of five percentage points across eight decisions.

19FollowingBertrand and Schoar 2003,our primary analyses are based on the managers position at the last firm. Whenwe require managers to retain the same job title at both Firm 1 and Firm 2i.e., CEO in both firms, CFO in both firms,or General Counsel in both firms, we still find that adding the manager-specific fixed effects increases the modelsadjusted R2 by an average of 8.3 raw percentage points across the five disclosure attributes.




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Table 4, replacing a manager at the 25th percentile with one at the 75th shifts away from a

tendency to issue forecasts to convey bad news, toward a tendency to issue forecasts to convey

good news. Table 5 shows that replacing a manager in the 25th percentile with one in the 75th

shifts from forecasts that undershoot earnings to forecasts that overshoot earnings. Finally, Table6shows that replacing a manager in the 25th percentile with one in the 75th increases average

absolute forecast error by 0.91 percent of stock price, which is material relative to the sample

mean absolute error of 0.58 percent per Table 1.

Taken together, Tables 26 show that manager-specific fixed effects play an economically

significant incremental role in explaining forecast frequency as well as detailed forecast attributes

such as precision, news conveyed by the forecast, bias relative to ex postactual EPS, and absolute

TABLE 3

Testing Individual Top Managers Fixed Effects on Forecast Precision

F_Precision(n 2,169)

a


Year- and Firm-Specific Fixed

Effects(Model 1)



Effects(Model 2)


Fixed Effects,Year- and Firm-

Specific FixedEffects

(Model 3)




Effects(Model 4)

Economic

DeterminantsandGeneral



Effects(Model 5)

Testing Economic Determinants 0

F-statistics 1.33 1.37 1.31 1.40 1.23


Testing Manager Fixed Effects 0

F-statistics 34.88 12.20 21.12 8.69

p-value 0.001 0.001 0.001 0.001

Constraints 235 138 84 17Adjusted R2 1.8% 10.0% 8.3% 3.8% 1.7%


As a % of Model 1s R 2 456% 361% 111% 6%


(n 235 Managers)

ManagerFixed Effect


Mean Effect 0.04

Median Effect 0.02

25th Percentile

0.3975th Percentile 0.36


0.75

aExhibit1 defines the economic determinants. Footnotes in Table2 explain the statistical tests.





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forecast error, increasing adjusted R2 by an average of 9.1 raw percentage points across the five

forecast attributes. Between 3851 percent of the individual managers fixed effects are statisti-

cally significant. These effects are economically significant. For example, replacing a manager at

the 25th percentile of forecast frequency with one at the 75th would more than triple the average

number of forecasts.20

20Focusing on managers who serve multiple employers is more conservative than using a full panel that includes allmanagerswhether they move. By observing Manager B in Figure1 only at Firm 1 in period 2, the effects of any

TABLE 4

Testing Individual Top Managers Fixed Effects on News Conveyed by the Forecast

Relative to Prevailing Analysts Forecasts

F_Goodnews(n 1,920)

a



Effects(Model 1)



Effects(Model 2)




(Model 3)




Effects(Model 4)




Effects(Model 5)

Testing Economic Determinants 0:

F-statistics 8.22 6.91 6.46 8.56 8.00


Testing Manager Fixed Effects 0:

F-statistics 184.86 50.19 81.35 1.69


Adjusted-R2 11.6% 21.1% 17.3% 16.2% 11.6%

Improvement in Adjusted R2 Relative to Model1:In Raw Percentage Points 9.5 5.7 4.6 0

As a % of Model 1s R 2 82% 49% 40% 0%


(n 214 Managers)

ManagerFixed Effect


Mean Effect 0.04

Median Effect 0.0325th Percentile 0.18



0.41






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Originating Source of Impetus for Deviations from the Firms Average Disclosure Policy

Tables26document the significant role individual managers unique styles play in explain-

ing deviations from the firms average voluntary disclosure policies. The question remains, how-ever, as to whether we can go further and shed light on the likely originating source of these

time-varying unobserved firm characteristics in period 2 would be attributed to Manager B, overstating Manager Bsfixed effect. Not surprisingly, when we repeat Models 15 using the full panel approach, including all firm-years withnecessary Execucomp/First Call data whether managers moved, and regardless of the length of time they spent at thefirm, the manager-specific fixed effects are, if anything, somewhat stronger.

TABLE 5

Testing Individual Top Managers Fixed Effects on Forecast Bias

Relative to Ex PostActual EPS

F_BiasUP(n 1,914)

a



Effects(Model 1)



Effects(Model 2)




(Model 3)




Effects(Model 4)




Effects(Model 5)


F-statistics 12.27 9.12 9.52 11.75 11.79



F-statistics 138.50 10.27 11.45 7.46


Adjusted-R2 12.5% 20.1% 16.7% 15.1% 12.9%


As a % of Model 1s R 2 61% 34% 21% 3%


(n 213 Managers)

ManagerFixed Effect


Mean Effect 0.01

Median Effect 0.0025th Percentile 0.50



0.96






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deviations. That is, do managers take the initiative to impose their styles on their firms, or do firms

hire managers because the firm wants the manager to bring his/her unique disclosure style whichwe refer to as the matching story? Under either scenario, managers influence the firms disclosure

choices. The only difference is the extent of the firms role in proactively hiring a manager with aparticular disclosure style.

We argue that the impetus likely stems from top managers independently imposing their styles

on the firm. First, Bertrand and Schoar 2003 conclude that the matching story does not explainthe significant manager-specific fixed effects on fundamental strategic and operational choices

such as preferences for internal versus external growth e.g., capital investments and R&D versusacquisitionsand financial aggressivenesse.g., dividend and capital structure policies. If firms do

TABLE 6

Testing Individual Top Managers Fixed Effects on Absolute Forecast Error

F_AbsError(n 1,914)

a



(Model 1)



(Model 2)


Fixed Effects,Year- and

Firm-SpecificFixed Effects

(Model 3)


andCFOs FixedEffects, Year-


Effects(Model 4)

Economic

DeterminantsandGeneral



Effects(Model 5)


F-statistics 6.72 5.82 6.37 5.95 6.84



F-statistics 51.50 6.75 13.78 3.12

p-value 0.001 0.001 0.001 0.001

Constraints 213 126 76 15Adjusted-R2 12.5% 22.8% 19.4% 14.0% 14.0%


As a % of Model 1s R 2 82% 55% 12% 12%


(n 213 Managers)

ManagerFixed Effect


Mean Effect 0.03

Median Effect 0.00

25th Percentile

0.4375th Percentile 0.48


0.91






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not proactively hire managers for specific styles in fundamental investment and operational deci-

sions, it stretches credulity that firms proactively hire new top executivesparticularly CEOs

largely to change attributes of voluntary management earnings forecasts. Second, respondents to a

recent National Investor Relations Institute NIRI survey say top managers do impose theirunique disclosure styles on the firm.21 Third, the matching story would require the firms desired

disclosure strategy to change over time in a pattern directly mirrored by changes in the types of

managers the firm hires, and the primary causes of changes in desired disclosure strategy would

have to be new drivers of voluntary disclosure that:1are not firm-specific characteristicswhichare controlled by the firm-specific fixed effects, 2 are not year-specific effects which arecontrolled by the year fixed effects, and3 have not been identified by prior research, and thusare not included in our vector of economic determinants.

Testing Whether Top Managers Personal Demographic Characteristics are Associated with

Their Unique Disclosure Styles

Table7provides descriptive statistics on our sample managers demographic characteristics.

Nearly half have an accounting or finance background, 8 percent have a legal background, and the

remainder rose from general management including production and marketing. Of the otherdemographic characteristics we measure, 16 percent of our sample managers were born before

World War II, 10 percent have military experience, and 37 percent hold an M.B.A.. We also

manually collected demographic characteristics of a random sample of 100 managers from the

Execucomp/First Call population of firms used for comparison in Table 1.Our sample managers

are not significantly different from the random sample, except that we have a smaller proportion

of older managers, which would bias against finding results on our age cohort variable PreWWII.Panel B shows that managers rising from accounting and finance are less likely to be born before

World War II, and more likely to hold M.B.A.s, consistent with a trend toward choosing profes-

sional administrators who run the company by the numbers.

Table 8 presents the results of estimating Model 6 that examines the association between

managers disclosure styles and their demographic characteristics. The base group impounded in

the intercept is managers born after World War II who have neither military experience nor an

M.B.A., and who rose from general management. Table8 shows that managers with accounting or

finance backgrounds develop disclosure styles that reflect lower tolerance of ambiguityfewer butmore specific forecasts, p 0.05 and that are conservative in tending to undershoot actualearningsp 0.04. Managers with legal backgrounds favor disclosure styles that guide expec-tations down p 0.09, reflecting sensitivity to litigation risk. Those born before World War IIare conservative in that they tend to issue fewer forecasts p 0.01. Managers with militaryexperience tend to develop disclosure styles that: 1are more precisep 0.04, reflecting lowertolerance of ambiguity, and2provide downwardnot upwardguidancep 0.02. Even thoughM.B.A.s disclosure styles tend to guide expectations up p 0.05, their disclosures are moreaccurate relative to ex postactual EPS p 0.08.

These associations between managers demographic characteristics and their fixed effects are

of interest in their own right. Finding plausible associations between manager-specific fixed effects

estimated in the first stage and distinctivepermanent characteristics of their own personal back-

21Among firms that discontinued guidance, the most popular response to What would make you consider providingearnings guidance in the future? was change in management philosophy. Similarly, when asked Where did thedecision to consider discontinuing guidance come from? 69 percent responded that it came from senior management.For companies that are currently providing guidance, but are considering discontinuing guidance, 63 percent of therespondents indicated that this is attributable to a change in management philosophy NIRI 2007.




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TABLE 7

Descriptive Statistics on Managers Personal Demographic Characteristicsa

Panel A: Frequency of Managers Demographic Characteristics

DemographicCharacteristics(n 292) Frequency Percent

Execucomp/FirstCall Random

Sample Percent


Acct/Fin 135 46 38

Legal 22 8 12

General Management 135 46 50

Age Cohort

PreWWII 48 16 31*Boomer/Xer 244 84 69*

Military Experience

Military 29 10 6

Non-military 263 90 94

M.B.A. Education

M.B.A. 107 37 29Non-M.B.A. 185 63 71

Panel B: Age Cohort, Military Experience, and M.B.A. Degree by Functional Career Track


Acct/Fin LegalGeneral

Management Total

By Age Cohort

PreWWII 15 4 29 48

Boomer/Xer 120 18 106 244

Total 135 22 135 292

Chi-Square Test of Independence: 2 2 5.34, p 0.07By Military Experience

Military 11 3 15 29Non-military 124 19 120 263

Total 135 22 135 292

Chi-Square Test of Independence: 2 2 1.03, p 0.60By M.B.A. Status:

M.B.A. 68 0 39 107

Non-M.B.A. 67 22 96 185

Total 135 22 135 292

Chi-Square Test of Independence: 2 2 27.18, p 0.001

* Indicates our sample differs significantly from the random sample managers n 100 selected from the Execucomp/First Call population on a two-sample test of differences in proportion p 0.05.a

We collect managers functional career tracki.e., employment history, age, military experience, and education fromMarquis Whos Who Online, Hoovers, Mergent Online, Zoominfo.com, NNBD.com, Execucomp, and general Internet

searches. We classify a managers functional background into one of three categories: Accounting and Finance Acct/Fin, Legal, or General Management including production, marketing, and strategy.




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grounds also confirms these fixed effects are not simply random, but instead capture systematic

long-lived cross-sectional differences in managers unique disclosure styles.

The explanatory power of these demographic characteristics is moderate, however.22

Two

econometric issues dampen the adjusted R2 from OLS estimation. First, the dependent variables in

Model 6 i.e., manager-specific disclosure styles are estimated parameters from the fixed-effectanalysis, and so contain measurement error although this measurement error should be smallerthan the error that would occur in simpler designs that do not cleanly separate the manager effect

from the firm effect. While OLS estimation still generates unbiased coefficients Wooldridge

22

While moderate, our adjusted R2s compare favorably to those of the only other study of which we are aware thatreports statistics on the explanatory power of models attempting to explain cross-sectional variation in managers fixedeffects or styles regarding other corporate decisions. In an independent and contemporaneously developed study,Dyreng et al.2010,1185document manager-specific effects on corporate tax avoidancemeasured based on effectivetax rates. They conclude that the results indicate that biographical information such as educational background and agedoes not explain much of the variation in tax avoidance across executives because adjusted R 2s from their regressionsare negative. However, the authors go on to point out that this finding does not suggest that executives have no effecton tax avoidance. Instead, these results are evidence that common, observable characteristics are not strongly associatedwith executives propensities to reduce effective tax rates.

TABLE 8

Testing Associations between Demographic Characteristics of Managers Personal

Backgrounds and Their Own Unique Overall Disclosure Stylesa

Model:m,Yi 0 1Acct/Fin 2Legal 3PreWWII 4Military 5MBA

F_Freq F_Precision F_Goodnews F_BiasUP F_AbsError

Acct/Fin 1 0.33 0.22 0.02 0.22 0.16

0.05** 0.01** 0.78 0.04** 0.15Legal 1 0.16 0.18 0.17 0.15 0.17

0.65 0.16 0.09* 0.43 0.50PreWWII 1 0.70 0.06 0.10 0.03 0.15

0.00*** 0.60 0.30 0.83 0.40Military 1 0.11 0.29 0.22 0.05 0.00

0.67 0.04** 0.02** 0.72 0.99

MBA

1 0.06 0.01 0.13

0.13

0.190.72 0.91 0.05* 0.20 0.08*Adjusted R2 OLS 3% 5% 7% 2% 1%

Robust Adjusted R2 LTSb 12% 13% 5% 9% 11%

*,**,*** Significant at 10 percent, 5 percent, and 1 percent, respectively.Two-tailed robust p-values adjusting for heteroscedasticity appear in parentheses.am,Yi are the manager-specific fixed effects estimated in Model 2. Acct/Fin, Legal, PreWWII, Military, and MBA a redichotomous variables characterizing whether managers rise from accounting/finance or legal backgrounds, whetherthey were born before World War II, whether they have military experience, and whether they hold an M.B.A. degree.To ensure our inferences are not an artifact of a few extreme values, we report OLS results after removing a smallnumber of extreme outliers withabsolute studentized residuals exceeding 2.

bRobust adjusted R2 is generated from the least trimmed squares robust regression Rousseeuw 1984.




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2006, 320, this larger error variance decreases R2. We ran a simulation to confirm that measure-ment error in the dependent variable can significantly dampen adjusted R2.

23

Second, measurement error in the dependent variable can lead to outliers. We repeat our

analysis using robust regression via least trimmed squares, which generates more stable results in

the presence of outliers Chen 2002;Zaman et al. 2001. The last row of Table8shows that forfour of our five forecast characteristics, the demographic variables explanatory power is quite a

bit higher using the robust regression estimation, with adjusted R2s ranging from 5 percent to 13

percent.

The simulation and robust regression results give a more appropriate sense of the economic

significance of the demographic characteristicsthe recommended starting point for exploring

differences in managers unique styles Finkelstein and Hambrick 1996; Hambrick 2007, 335.Although we conducted a comprehensive review of a broad range of literatures, theory as to how

demographic characteristics might be associated with unique managerial styles is in its infancy,

and there are a limited number of observable permanent demographic characteristics that couldplausibly affect disclosure. Managers individual-specific disclosure styles undoubtedly result

from their many unobservable experiences, psychological traits, and values, for which demo-graphic characteristics such as functional career track, age cohort, military experience, and M.B.A.

education provide a start, but are admittedly an incomplete and crude set of proxies.

Additional Analyses

Given the modest explanatory power of the demographic variables, we also explore whether

two nondemographic factors explain managers disclosure styles: managers risk-taking behavior

as revealed by their fixed effects on their firms operating and financing decisions, and managers

fixed effects on their firms operational efficiency.24

We identify firm decisions and outcomes that

might reflect their managers risk-taking behavior: the frequency of acquisitions, investment in

R&D and capital expenditure, cash holdings, and stock return volatility Bertrand and Schoar2003;Bargeron et al. 2010. We estimate managers fixed effects on these decisions and outcomesusing models similar to Bertrand and Schoar 2003. We add these risk-related manager-specificfixed effectsindividually and in a composite index to our original set of demographic variablesin Model 6 that explains managers overall disclosure styles. Our original inferences remain

largely robust, and we find little evidence that these risk-related manager-specific fixed effects are

associated with managers styles in voluntary disclosure.25

23Even in a simulated world where X fully explains the true value of Y so R2 is 100 percent absent measurement error,adjusted R2 plummets from 97 percent when the stand

bamber et al. 2010 styles

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