CEO Narcissism and Management Forecasting
1. Introduction
This paper investigates one import personality trait of CEOs, narcissism, and its impact on
corporate voluntary disclosure practice, management earnings forecasts. Researchers have foundthat individual’s psychological characteristics affect capital markets and organizational policies(Daniel et al., 1998; Kyle and Wang, 1997; Libby et al., 2002). Narcissism, as one of the mostvivid qualities seen in CEOs, has gained researchers’ attention recently. Campbell et al. (2004)
show that narcissists are generally risk lovers. Chatterjee and Hambrick (2007) further show thatnarcissistic CEOs generally favor bold actions that attract attention, resulting in large variance infirm performance. Recent studies also show that CEO narcissism affects earnings management
practice (Ham et al., 2015; Rijsenbilt and Commandeur, 2013). Yet little has been down on theimpact of CEO narcissism on corporate voluntary disclosure, specifically on management
earnings forecasts. Management forecasts, as one of the most important information channel forinvestors (Beyer et al., 2010), gather great amount of attention from investors, analysts, andregulators, which provides a perfect stage for narcissistic CEOs to draw attention, envy, andadmiration, and reaffirm their self-superiority. On the other hand, due to their arrogance, fantasy
thinking, and lack of empathy, narcissistic CEOs may not provide useful forecasts to investors.
Therefore, management forecasts provide a unique and interesting setting to examine narcissistic
CEOs decision making.
Narcissism is a multidimensional personality. Emmons (1987) have identified four key
factors of narcissism: (1) Exploitativeness/Entitlement (I insist upon getting the respect that isdue to me); (2) Leadership/Authority (I like to be the center of attention); (3)Superiority/Arrogance (I am better than others); and (4) Self-absorption/Self-admiration (I am1

preoccupied with how extraordinary and special I am). Prior studies in psychology haveconcluded that narcissism is traceable to a combination of genetic factors and early parental
relations (Chatterjee and Hambrick, 2007; Hotchkiss, 2003; Livesley et al., 1993). Narcissism isrelated to but distinct from the construct of overconfidence. While overconfidence results fromover estimating one’s abilities and skills due to positive past experiences or previous success andillustrates unrealistically optimistic views about uncertain outcomes, on the other hand,
narcissism is thinking that one is superior and omnipotent. First of all, overconfidence isprimarily triggered by external stimuli, but the self-importance aspect of narcissism, which iscorrelated with overconfidence, is an internal disposition. Second, overconfidence lacks key
elements of the narcissistic personality, a sense of entitlement, preoccupation with self, andcontinuous need for affirmation and applause (Chatterjee and Hambrick, 2007). Prior studies
have examined the association between overconfidence and management forecasts and find that
overconfident CEOs have larger likelihood of issuing management forecasts, tend to issue
optimistic forecasts and tend to underestimate the uncertainty and issue more precise forecasts(Hribar and Yang, 2015; Libby and Rennekamp, 2012). While overconfident CEOs have theconventional rational utility functions, narcissistic CEOs’ utility is primarily towards selfreaffirmation. Therefore, how narcissistic CEOs make decisions regarding management forecasts
is still worth exploring.
Our paper investigates the impact of CEO narcissism on management forecasts in three
aspects: (1) the decision to make a forecast, (2) the precision of the forecast, and (3) the accuracyof the forecast. Specifically, we examine whether narcissistic CEOs are more likely to issue
management forecasts to attract attention, whether narcissistic CEOs are making bold yet precise
forecasts, and whether narcissistic CEOs inflate forecast.

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We measure CEO narcissism using the empirical measure developed by Chatterjee andHambrick (2007), the use of first-person singular pronouns relative to the use of first-person
plural pronouns in public speeches. This measure well captures the key elements of the four
aspects of narcissistic personality, and can be constructed on a large sample. We start with
Compustat Execucomp firms and then extract transcripts for all conference calls andpresentations in which these firms are involved from Factiva and conduct a textual analysis. The
narcissism measure is calculated as the ratio of the number of first person singular pronouns(e.g., I, me, my, mine, myself) to the total number of first person singular plus plural pronouns(e.g., we, us, our, ours, ourselves) in CEO’s speeches. Our sample consists of primarily large US
public firms, namely, S&P1500 firms for the period 2002 to 2013. To draw distinction fromoverconfidence, we include overconfidence as a control variable. We calculate the averagemoneyness of the CEO’s option portfolio for each year and classify CEOs as overconfident if
they hold options with average moneyness of at least 67 percent more than once before thecurrent year, following Campbell et al. (2011), Hirshleifer et al. (2012), and Hribar and Yang
(2015).
We find that CEO narcissism is negatively associated with the likelihood of issuingmanagement forecasts and the frequency of management forecasts, negatively associated with
forecast precision, positively associated with optimistic bias, positively associated with forecast
accuracy, and positively associated with the likelihood of extreme news contained in theforecasts. We also find that the negative relation between CEO narcissism and likelihood andfrequency of management forecasts is mitigated by extreme earnings news. Specifically, we findthat narcissistic CEOs are more likely to issue forecasts when the underlying earnings news is
extreme, particularly extreme good. Our evidence paints a coherent view of the behavior of3

narcissistic CEOs. On one hand, that narcissistic CEOs are lack of empathy for investors’
information demand and lack of commitment for establishing routine forecasting policies, andtheir self-admiration and sense of superiority drives them to avoid possible unfavorable outcome,specifically missing the forecast, at all costs, and therefore they are reluctant to issue forecasts,
and only issue forecasts when uncertainty is lower and accuracy is higher, and issue less precise
forecasts. Yet narcissistic CEOs’ hunger for grandiosity and public attention leads to issuingmanagement earnings forecasts when the underlying earnings news is more extreme and toissuing forecasts containing more extreme surprise to the markets. We further investigate
whether CFO narcissism has similar impact on management forecasts, but we do not findsignificant results. In contrast, CEO overconfidence does not load in the majority of the analyses.
Our results are robust to different model specifications and samples.
Prior studies have shown that CFO also plays a key role in financial reporting andvoluntary disclosure (Ge et al., 2011; Jiang et al., 2010). We therefore further investigate
whether CFO narcissism has impact on management forecasts, but we do not find significant
relations.
Our results have important implications for understanding managers’ decision making
process. In deciding on voluntary disclosure, managers are concerned with setting disclosure
precedents that cannot be maintained, which in turn impedes voluntary disclosure (Graham et al.,2005; Libby and Rennekamp, 2012). Failing to maintain the disclosure precedents may cause
damage to a CEO’s reputation and image, which is an even bigger concern for narcissistic CEOs
because attention and admiration is one of the biggest drivers for them. Narcissistic CEOs tend to
make management forecasts only when the forecast can in turn enhance the CEOs’ superiority
image, i.e., when the forecast can be made relatively more accurate and more optimistic.
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Our paper contributes to several streams of literature. First, our paper adds to the growing
literature on narcissism and corporate decision making. Prior studies have documented thatnarcissism is an important personality trait that affects risk-taking behavior, mergers andacquisitions, and earnings management (Amernic and Craig, 2010; Campbell et al., 2004;
Chatterjee and Hambrick, 2007; Ham et al., 2015; Ham et al., 2014; Rijsenbilt and Commandeur,2013). Our paper adds to the existing evidence by showing that narcissistic CEOs makemanagement forecast decisions differently than non-narcissistic CEOs. We also show that it’s
CEO narcissism, not CFO narcissism, that plays a role in management forecasting decisions. We
further show the distinction between narcissism and overconfidence. In management forecasting
decision, CEO narcissism dominates CEO overconfidence. This is also consistent with the viewthat narcissism is a more fundamental, ingrained property, while overconfidence is a presentativeand variable characteristic.
Second, we contribute to the literature on management forecasts. We document that CEO
narcissism plays a significant role in management forecasting decision, and in choice of forecast
characteristics. Our paper answers the call for studies on understanding managers’ choice of
forecast characteristics by Hirst et al. (2008). Our evidence shows that narcissistic CEOs tend to
make less precise, more optimistic, yet more accurate forecasts.
The rest of the paper is organized as follows. In the next section, we review the literatureand lay out our hypotheses. Section three presents our research design and sample selection.
Section four shows the empirical results, and section five concludes our paper.

2. Literature and Hypotheses

52.1 Narcissism
According to the Diagnostic and Statistical Manual of Mental Disorders (DSM),
narcissism is defined as ‘‘a pervasive pattern of grandiosity (in fantasy or behavior), need foradmiration and a lack of empathy, beginning by early adulthood and present in a variety ofcontexts’’ (American Psychiatric Association, Task Force on DSMIV., (2000), p. 717).
Narcissism is generally viewed as genetic but evolves with life experience and surrounding
stimuli (Campbell et al., 2002; Freud, 1914). Emmons (1987) have identified four key factors ofnarcissism: (1) Exploitativeness/Entitlement (I insist upon getting the respect that is due to me);(2) Leadership/Authority (I like to be the center of attention); (3) Superiority/Arrogance (I ambetter than others); and (4) Self-absorption/Self-admiration (I am preoccupied with how
extraordinary and special I am). On the cognitive, narcissism entails a belief in one’s superior
qualities. On the motivational side, narcissism carries an intense need for other people’s
affirmation, applause, and admiration. So, paradoxically, the self-admiring narcissist craves
further admiration (Chatterjee and Hambrick, 2007). And the craving for admiration iscontinuous, meaning that the narcissist requires a steady stream of self-image reinforcement(Kohut and Wolf, 1986). To obtain such applause and attention, the narcissist may undertake
highly visible tasks, frequently. The narcissist, however, is especially susceptible to criticism,and tend to ignore the feelings, words, and behaviors of others and therefore is lack of empathy(Rijsenbilt and Commandeur, 2013).
Narcissism is related to but distinct from the construct of overconfidence. While
overconfidence results from over estimating one’s abilities and skills due to positive pastexperiences or previous success and illustrates unrealistically optimistic views about uncertain
outcomes, on the other hand, narcissism is thinking that one is superior and omnipotent. First of6

all, overconfidence is primarily triggered by external stimuli, but the self-importance aspect ofnarcissism, which is correlated with overconfidence, is an internal disposition. Second,
overconfidence lacks key elements of the narcissistic personality, a sense of entitlement,
preoccupation with self, and continuous need for affirmation and applause (Chatterjee andHambrick, 2007).
CEOs tend to be more narcissistic than the general population, as Kets de Vries (2004)
says that “narcissism lies at the heart of leadership”. The great power and influence of CEO
positions may provide a steady narcissistic supply, which in turn drive narcissists to pursue andretain CEO positions. Prior papers have examined the CEO narcissism on risk-taking behavior
and earnings management.
Chatterjee and Hambrick (2007) construct a CEO narcissism measure based on the sizeof the CEO’s photograph in annual reports, the CEO’s prominence in media, use of first-person
singular pronouns in interviews, and compensation relative to the second-highest-paid executive,and examine the effect of CEO narcissism on firm strategy and performance. They find that theirnarcissism measure is quite stable and consistent with scores based on survey. Using a sample of
111 CEOs in 1992 – 2004, they show that CEO narcissism is positively associated with strategic
dynamism and grandiosity, number and size of acquisitions, and extreme firm performance. Ham
et al. (2014) measure narcissism using the size of CEO signatures in annual report and show that
CEO narcissism is associated with overinvestments, lower innovation, and worse firm
performance, yet narcissistic CEOs receive higher compensation.
Rijsenbilt and Commandeur (2013) use narcissism scores obtained from a factor analysisof 15 variables to investigate the effect of CEO narcissism on the SEC Accounting and Auditing
Enforcement Releases (AAER) fraud. They find a positive relation between CEO narcissism and7the likelihood of AAER fraud, and conclude that the pursuit of narcissistic supply result in a
CEO undertaking unethical decisions. Similarly, Ham et al. (2015) find that CFO narcissism ispositively associated with earnings management, lower conservatism, weaker internal control,
and financial restatements, using signature size in annual reports as a narcissism measure.
Two related studies have examined CEO overconfidence and management forecasts.
Using an experiment and survey, Libby and Rennekamp (2012) show that overconfidence
increases the likelihood of issuing management forecasts. Hribar and Yang (2015) use
overconfidence measures constructed based on option and press coverage, and find that
overconfidence increases the likelihood of issuing management forecasts, increases optimism,
and increases precision of management forecasts. While narcissism is correlated withoverconfidence, they are distinct constructs. Campbell et al. (2004) argue that narcissism, as afundamental personality, leads to overconfidence and risk-taking behavior. The entitlement senseof a narcissist may come out of no reason, and a narcissist may be lack of self-confidence andtherefore try to compensate this shortcoming by presenting himself as being more important thanand superior to others. Due to the uniqueness and paradox of narcissism, its effect onmanagement forecast may be very different from overconfidence. We will lay out our hypotheses
as follows respectively.

2.2 Hypotheses
Prior studies on management forecasts have investigated incentives for and constraints on
management forecasts: proprietary costs (Verrecchia, 1983), litigation risk (Skinner, 1997),
personal wealth maximization (Nagar et al., 2003), career concerns (Cotter et al., 2006),

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corporate governance (Ajinkya et al., 2005). CEO personality traits, particularly narcissism can
influence management forecast decisions. On one hand, narcissistic CEOs are exhibitionists(Raskin and Terry, 1988). They constantly seek attention and admiration of others. Management
forecasts, as one of the most important information sources for investors (Beyer et al., 2010),
provide a venue for attention and visibility. Making management forecasts provides narcissistic
supply and therefore narcissistic CEOs are more likely to issue and more frequently issue
management forecasts. On the other hand, narcissistic CEOs are fragile in that external criticism
can cause a down hit to narcissistic CEOs and they try to avoid criticism and shame at all costs.
Furthermore, narcissistic CEOs lack empathy, tend to ignore the demand of investors for more
information, and thus are reluctant to make voluntary management forecasts. Narcissists are alsolack of commitment in interpersonal relationships (Campbell and Foster, 2002). Narcissistic
CEOs, therefore, are reluctant to issue management forecasts which could lead to market’s
expectation of a routine management forecast policy. In addition, narcissistic CEOs favor
grandiosity and drama and are easily bored of small numbers and routine actions. Therefore, thethreshold for narcissistic CEOs to make earnings forecasts are higher, which suggests that thelikelihood and frequency of issuing management forecasts is lower. Furthermore, when the
narcissistic CEO’s private information tells that the earnings performance is more dramatic andeye-catching, he will be more willing to make a forecast about the dramatic earnings, to feed hisdesire for grandiosity and investors’ attention. We therefore hypothesize that:
Hypothesis 1a: A more narcissistic CEO is more likely to issue management forecasts.
Hypothesis 1b: A more narcissistic CEO makes more frequent management forecasts.
Hypothesis 1c: A more narcissistic CEO is more likely to issue management forecasts whenearnings change is more extreme.
9Narcissists are so fragile to criticism from others that they try to avoid criticism at all
costs. When making management forecasts, narcissistic CEOs tend to reduce criticism/shame
due to missing the forecast. Reducing the precision/specificity of the forecast is a safe way of
avoiding missing the forecast. Making a range forecast instead of a point forecast easily reduces
the risk of missing the forecast. On the other hand, narcissistic CEOs tend to be overconfident,
which leads the CEOs to underestimate the variance of the forecasted performance and to believethat they can more precisely forecast the future performance (Hribar and Yang, 2015). We
therefore hypothesize that:
Hypothesis 2: CEO narcissism is negatively associated with the precision of management
forecasts.
Narcissists tend to engage in bold, attention-catching behaviors to grasp attention andadmiration of others (Campbell et al., 2004; Wallace and Baumeister, 2002). Providing a forecast
that is expected and no surprise does not cause enough attention from the investor audience andthus does not supply to the needs of narcissistic CEOs. Furthermore, narcissistic CEOs need
constant applause and admiration from the investor audience. Providing a pessimistic forecast
will not create applause or admiration. Therefore, narcissistic CEOs are more likely to issue bold
optimistic forecasts. On the other hand, missing the forecast target may cause damage to theCEO’s reputation, and this is particularly true for narcissistic CEOs since they care more about
their self-image and any shame/criticism will cause a devastating pain to them (Hotchkiss, 2003).
Therefore, narcissistic CEOs are more likely to issue more accurate forecasts. We hypothesize
that:
Hypothesis 3a: CEO narcissism is positively associated with the optimism of management
forecasts.
10Hypothesis 3b: CEO narcissism is negatively associated with the accuracy of management
forecasts.

3. Research Design
3.1 Measurement of narcissism
Lying in the center of narcissism is the notion of “all about me” (Hotchkiss, 2003), andtherefore the use of first-person singular pronouns, reflecting self-absorption, a sense of
superiority, and a sense of entitlement, is an indicator of narcissism (Chatterjee and Hambrick,
2007; Raskin and Shaw, 1988). We measure narcissism with the use of first-person singularpronouns in CEOs’ public speeches during conference calls, similar to Chatterjee and Hambrick(2007). Our choice of conference call speeches is based on the fact that speech is a form of
express behavior which reflects the most dominant and consistent personality traits of anindividual (Ramsay, 1968), and that conference calls provide a homogenous context of businesslanguage to all CEOs, in which the language choices are comparable across CEOs (Duranti andGoodwin, 1992; Handford, 2010; Loughran and McDonald, 2011). We first extract 145,534
transcripts for all conference calls and presentations from Factiva and SeekingAlpha in the
period 2002 to 2014. We start from 2002 because the coverage in Factiva starts in 2000 and only
becomes comprehensive in 2002. We then merge these transcripts Compustat ExecuComp,
namely S&P 1,500 companies, using company and executive names, and obtain 64,425 uniquetranscripts for 2,317 companies. We then isolate only those words of CEO talks, and count the
number of first-person singular pronouns (I, me, my, mine, myself) the CEO uses, divided by thesum of those pronouns plus the number of first-person plural pronouns (we, us, our, ours,

11ourselves). For a given year t, we take an average of the ratio over the prior three years to get ourmeasure of narcissism. We construct the narcissism measure for CFOs similarly. Finally weobtain speeches for 12,061 CEOs and CFOs. Chatterjee and Hambrick (2007) conduct a validity
test for this measure and find that it is consistent over time for each individual but varies greatly
over time for each company, suggesting that this measure captures CEO narcissism instead ofcorporate narcissistic culture. We also conduct our own validity test and find that the narcissism
measure has a high autocorrelation (Pearson correlation of 0.86) for each individual. We
alternatively measure narcissism using all speeches made by an individual during our sample
period and this alternative measure has a correlation of 0.88 with the 3-year average measure.
We also identify 28 CEOs that serve in more than two companies and the correlation of
narcissism across companies is as high as 0.80. On the other hand, we identify 785 firms thathave at least CEO turnovers and the correlation of narcissism across CEOs for such companies is
as low as 0.26. This suggests that our narcissism measure better captures the characteristic of a
CEO other than a company.
The self-admiration dimension of narcissism could be correlated overconfidence(Campbell et al., 2004), and CEO overconfidence is associated with management forecasts(Hribar and Yang, 2015; Libby and Rennekamp, 2012). To isolate the effects of narcissism fromoverconfidence, we control for CEO overconfidence in our analyses. Following Hribar and Yang
(2015), we construct an overconfidence indicator variable based on CEO vested option holdings
reported in Compustat ExecuComp. Specifically, we first estimate, for each year t, the realizablevalue per option as the total realizable value of options divided by the number of exercisable
options. We then estimate the average striking price as the market price of the stock at year t end
minus the realizable value per option. The ratio between the realizable value per option to12average striking price is the average moneyness of the option. If a CEO holds vested options
even when the average moneyness of the option is above 67% for at least twice end year t, we
code this CEO an overconfident CEO.
3.2 Sample selection and variable definitions
We start our sample with the Compustat ExecuComp dataset in the period 2002 – 2013,
with transcripts available from Factiva and SeekingAlpha. Our management forecast data are
extracted from First Call CIG database and I/B/E/S Guidance Detail database. The First Call CIG
database was discontinued by year 2011 and I/B/E/S Guidance Detail database is provided as a
substitute since then by the same data provider Thomson Reuters. We combine these two
databases and conduct our analyses based on annual forecasts from the combined dataset. We
obtain corporate financial information from Compustat Fundamentals, stock market data from
CRSP, institutional holding data from Thomson-Reuters Institutional Holdings (13F) Database,and data on board of directors from BoardEx. Our final sample consists of 27,743 management
forecasts made for 11,447 firm-years during the period 2003 – 2013.
Table 1 reports the sample distribution over time. The CEO narcissism measure isrelatively stable over time, between 0.19 and 0.20. The CEO overconfidence measure constantly
increases over time, consistent with Hribar and Yang (2015). The different patterns of narcissism
and overconfidence is possibly due to that narcissism is an innate and persistent personality
while overconfidence is gained over past experience and manifests itself over time. The
percentage of companies issuing management forecasts and frequency of management forecasts
are generally consistent with prior studies.

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We investigate management forecasting decisions in the following aspects: likelihood of
issuing a forecast (Issue), frequency of forecasts (Freq), the precision/specificity of forecasts(Specificity), and bias (Miss and Bias) and accuracy (Error) of forecasts. Issue = 1 if firm makes
at least one management earnings forecast during the fiscal year t, and 0 otherwise. Freq = thenumber of management earnings forecasts made during the fiscal year t. Specificity is an orderednominal variable which takes a value of 3 if the firm issued a point forecast during a fiscal
period, 2 if an interval forecast, 1 if an open-ended forecast, and 0 if a qualitative forecast. Miss
= 1 if actual earnings is less than the management forecast, and 0 otherwise. For range forecasts,
Miss = 1 if actual earnings is less than the lower bound of the range estimate. Bias =[(management forecast of EPS − actual EPS)/logged assets per share at the beginning of the
fiscal period]. If Bias > 0, the earnings forecast is optimistically biased. Error = absolute value[(management forecast of earnings per share (EPS) − actual EPS)/ logged assets per share at the
beginning of the fiscal period]. Accuracy of forecasts is the inverse of Error. We also control forforecast horizon and forecast news, where Horizon = number of days between the forecast date
and the fiscal period-end date, and News = Management forecast of EPS – analysts’ consensus
forecast of EPS prior to management forecast, scaled by logged assets per share.
Table 2 reports the summary statistics for CEO narcissism, overconfidence, andmanagement forecast characteristics. The mean CEO narcissism is 0.193, and the mean
overconfidence is 0.405. The average number of management forecasts issued each year is 1.9,
and on average 44.7% companies issue management forecasts each year. A typical management
forecast is a range forecast (Specificity = 2), 31% of management forecasts are optimistic, andthe mean forecast bias is pessimistic -0.048. The mean forecast error is 0.107. The mean forecasthorizon is 196 days, and on average the forecast contains bad news to the market.

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Table 3 reports the Pearson correlation between CEO narcissism, overconfidence, andmanagement forecast qualities. Overall CEO narcissism is negatively correlated withoverconfidence, and the correlation between CEO narcissism and forecast qualities is in the
opposite direction to the correlation between CEO overconfidence and forecast qualities. For
example, CEO narcissism is negatively associated with Issue and Freq while overconfidence isnegatively associated with these two variables. These correlations, however, are general small inmagnitude.

4. Empirical Results
4.1 Main results
To test Hypothesis 1a, we estimate a logit model predicting the likelihood of issuing aforecast, Issue:
Logit(Issue) = β0 + β1 Narci_CEO + β2 OverConf + β3 CEOTenure + β4 logCashComp +β5 logEquityComp + β6 InstHolding + β7 OutDir + β8 logNAF + β9 logMV + β10
BM + β11 EarnVol + β12 Litigate + β13 ChgEarn + β14 Loss + β15 CEOHolding +β16 ROA + β17 Beta + β18 Idiosync + Industry & Year Fixed Effects + ε(1a)And for Hypothesis 1b, we estimate a multivariate linear model of frequency of management
forecasts (Freq) on the same set of independent variables.
Freq = β0 + β1 Narci_CEO + β2 OverConf + β3 CEOTenure + β4 logCashComp + β5
logEquityComp + β6 InstHolding + β7 OutDir + β8 logNAF + β9 logMV + β10 BM

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+ β11 EarnVol + β12 Litigate + β13 ChgEarn + β14 Loss + β15 CEOHolding + β16
ROA + β17 Beta + β18 Idiosync + Industry & Year Fixed Effects + ε(1b)The coefficient β1 is of our interest for testing Hypothesis 1a. We control for CEO tenure(CEOTenure) which is measured as number of years the CEO has been in position, because priorstudies have shown and CEO tenure is associated with CEO power and incentives and therefore
affects corporate financial reporting and disclosure decisions (Ali and Zhang, 2015; Hui, 2004).
We also control for CEO incentives as measured by the natural log of cash compensation(logCashComp) and the natural log of equity compensation (logEquityComp), since prior studies
have found that CEOs strategically make disclosure decisions to maximize personal wealth(Aboody and Kasznik, 2000; Nagar et al., 2003). CEO compensation is also argued to becorrelated with CEO narcissism (Chatterjee and Hambrick, 2007; Rijsenbilt and Commandeur,2013), and therefore omission of compensation variables will possibly cause omitted correlated
variables problem. We also control for percentage of outstanding shares held by CEOs
(CEOHolding) since it helps align CEOs’ interest with shareholders and incentivize CEOs todisclose, and it is correlated with CEO overconfidence (Malmendier and Tate, 2005). We control
for institutional holding (InstHolding) and the percentage of independent directors on board(OutDir), as Ajinkya et al. (2005) have documented that firms with greater institutional holding
and more independent directors are more likely to provide management forecasts and theirforecasts are more accurate and precise. We next control for firm information environments.
Managers of firms with greater analyst following (logNAF) and of greater size (logMV), face agreater demand for information and are likely to provide more voluntary disclosure (Ajinkya andGift, 1984; Hutton, 2005; Lang and Lundholm, 1996). We also control for earnings volatility
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(EarnVol), market beta (Beta) and idiosyncratic risk (Idiosync), as Waymire (1985) finds thatfirms with higher uncertainty as measured by higher earnings volatility are less likely to issue
management forecasts, Bushee and Noe (2000) find that association between corporate
disclosures and market risk, and Ajinkya et al. (2005) find that market beta is negatively
associated with the likelihood of issuing a forecast, forecast frequency, and specificity. We
control for litigation risk (Litigate), as Skinner (1997) argues that firms make voluntary
disclosures to reduce litigation risk. We lastly control for book-to-market ratio (BM) which
proxies for growth and proprietary costs (Bamber and Cheon, 1998), and performance measured
as return on assets (ROA), change in earnings (ChgEarn), and an indicator for loss (Loss), as
Miller (2002) shows that performance is negatively associated with voluntary disclosures.
Detailed variable definitions are listed in the appendix. The summary statistics for these control
variables are reported in table 2, and are generally consistent with prior studies (Ajinkya et al.,2005; Hribar and Yang, 2015), except that institutional ownership and analyst following areslightly higher due to that our sample contains larger firms and more recent years.
Table 4 reports the estimation of models (1a) and (1b). In panel A of table 4, we estimate
the logit model (1a). We first include CEO narcissism and overconfidence independently andthen include both. Across all specifications, CEO narcissism loads significantly and negatively,
and CEO overconfidence remains insignificant consistently. In column (4), including further
controls on CEO tenure and compensation, the magnitude and significance of CEO narcissism
decreases a little but still significant at 1% confidence level with a coefficient of -3.204 and tvalue of -4.93. The coefficient of -3.204 suggests that one standard deviation increase in CEO
narcissism from sample mean is associated with 7% increase in likelihood of issue amanagement forecast. The coefficient of CEO overconfidence, although insignificant, is positive,

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consistent with Hribar and Yang (2015). Consistent with prior studies, independent directors(OutDir) and analyst following (logNAF) have significant positive coefficients, while earnings
volatility (EarnVol), change in earnings (ChgEarn), loss dummy (Loss), CEO holding(CEOHolding), market beta (Beta), and idiosyncratic risk (Idiosync) have significant negative
coefficients.
Table 4 panel B reports estimation for model (1b). The results are consistent with panel
A. CEO narcissism loads consistently significantly and negatively, while overconfidence has ainsignificant but positive coefficient. The coefficient of CEO narcissism is -2.715 with a t-valueof -4.80 in column (4) when all controls are included, suggesting that increase of one standard
deviation in CEO narcissism is associated with an increase of 0.18 forecasts, after controlling
everything else. The evidence in table 4 panels A and B rejects Hypotheses 1a and 1b,
specifically, CEO narcissism is negatively associated with the likelihood and frequency of
issuing management forecasts.
We further investigate whether the mitigating effects of extreme earnings news are due toextreme good earnings news or extreme bad earnings news. We create indicators for extreme
good news XGoodEarn and for extreme bad news XBadEarn, and then interact them with CEO
narcissism. We report the results in columns (5) and (6) of panels A and B in table 4. We findthat both XGoodEarn and XBadEarn have negative main effects for Issue and Freq. Theinteraction terms are significant at 5% confidence level and positive, except the interaction of
extreme bad news and CEO narcissism in the logit regression of Issue dummy. The evidence incolumns suggests that the mitigating effects of extreme earnings news exist for both extreme
good news and extreme bad news, but are more pronounced for extreme good news, consistent
with the view that a narcissistic CEO enhances his self-image and self-admiration by providing
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grandiose forecasts and particularly positive grandiose forecast and attracting attention andapplause.
4.2 CEO narcissism and the qualities of management forecasts
We next test the qualities of forecasts regarding Hypotheses 2, 3a and 3b. In thefollowing tests, we use all forecasts made a firm in the year t. 1 To test Hypothesis 2, we estimate
an ordered logit model of forecast specificity on CEO narcissism:
Ologit(Specificity) = β0 + β1 Narci_CEO + β2 OverConf + β3 CEOTenure + β4
logCashComp + β5 logEquityComp + β6 InstHolding + β7 OutDir + β8 logNAF +β9 logMV + β10 BM + β11 EarnVol + β12 Litigate + β13 ChgEarn + β14 Loss + β15
CEOHolding + β16 ROA + β17 Beta + β18 Idiosync + β19 DAcc + β20 News + β21logHorizon + Industry & Year Fixed Effects + ε(2)

Besides the controls in models (1a) and (1b), we further control for discretionary accruals (DAcc)
estimated from the modified Jones model, as Kasznik (1999) finds that firms tend to manage
earnings to meet their own forecasts, forecast news (News) and horizon (logHorizon), as
forecasts issued later in the periods should be subject to less earnings uncertainty and, thus, aremore likely to be precise (Ajinkya et al., 2005; Choi et al., 2010), and news amount is positively
associated with forecast error and bias and thus precision (Ajinkya et al., 2005).
The results are presented in table 5. Consistent with our prediction, the coefficient of
CEO narcissism is significant and negative, -1.256 with t-value of -2.07, suggesting higher CEO
narcissism is associated with less precise forecasts. Forecast horizon loads significantly and1

Alternatively, we keep only the last forecast made by a firm in a given fiscal year, and our results do notchange significantly.

19negatively, suggesting that the earlier the forecast is made, the more uncertainty the CEO has andthus less precise the forecast is. Institutional holding loads significantly and positively, while
director independence loads negatively, generally consistent with Ajinkya and Gift (1984). In
contrast, CEO overconfidence does not load significantly.
We next test our Hypotheses 3a and 3b. We measure forecast optimism using an indicatoron whether management forecast is higher than actual earnings (Miss) and the difference
between management forecasts and actual earnings, scaled by logged total assets per share(Bias). And we measure forecast accuracy using the absolute value of the difference between
management forecasts and actual earnings (Error). We estimate a logit model of Miss and linear
models for Bias and Error:
logit(Miss)/Bias/Error = β0 + β1 Narci_CEO + β2 OverConf + β3 CEOTenure + β4
logCashComp + β5 logEquityComp + β6 InstHolding + β7 OutDir + β8 logNAF +β9 logMV + β10 BM + β11 EarnVol + β12 Litigate + β13 ChgEarn + β14 Loss + β15
CEOHolding + β16 ROA + β17 Beta + β18 Idiosync + β19 DAcc + β20 News + β21logHorizon + Industry & Year Fixed Effects + ε(3)The estimation results are reported in table 6. Column (1) reports the logit regression ofMiss, column (2) reports the linear regression of magnitude of Bias, and column (3) reports thelinear regression of forecast Error. Consistent with our Hypothesis 3a, CEO narcissism ispositively associated with the likelihood of issuing an overoptimistic forecast. The coefficient of
CEO narcissism is 1.065, significant at 5% confidence level, in column (1). The coefficient of
CEO narcissism, although positive, is insignificant when the magnitude of Bias is regressed incolumn (2). The coefficient of CEO narcissism loads significantly and negatively in the
regression of forecast Error, -0.049 with t-value of -2.34, in the opposite direction to our20

prediction. The coefficient suggests that an increase of one standard deviation in CEO narcissism
is associated with a decrease in 0.003 in forecast error, which is equivalent to a 7% decrease in
the mean forecast error. The evidence in table 6 suggests that narcissistic CEOs are in a paradoxof concerns about criticism from missing the forecast and craving for grandiosity of boasting
forecasts. Narcissistic CEOs are concerned about missing the forecast and therefore only issue
forecasts when the uncertainty is relatively small and the forecast can be reasonably made, yetthey crave for grandiosity and therefore tend to forecast optimistically. CEO overconfidence
does not consistently load. It loads negatively for Miss only, and its coefficients are consistently
in the opposite direction to CEO narcissism.
The evidence in tables 4 to 7 coherently draw the picture of narcissistic CEOs. Root in
the self-admiration and sense of superiority, narcissists are so intolerant of shame/criticism thatthey try their best to avoid shame and not to experience it at all. What psychologists call“bypassed shame” is hiding behind the coldness, lack of empathy, and exploitativeness ofnarcissists (Hotchkiss, 2003). And narcissists are less likely to make commitment ininterpersonal relationships (Campbell and Foster, 2002). In the decision-making process of
issuing management forecasts, narcissistic CEOs tend to avoid making forecasts that could
possibly be missed. They are not as likely to issue forecasts as non-narcissists, likely to issue
forecasts less frequently, and only likely to issue forecasts when the uncertainty is relatively low.
Yet their craving for grandiosity leads to optimistic forecasts given the decision to issue
forecasts.
4.3 Additional analyses
Our measure of narcissism has two possible issues. One issue is that it may capture thenarcissistic organizational ideal/culture of the company since the conference calls are in21

corporate context. Through a validity test, we have found that our narcissism measure is highly
persistent for a particular individual, but much more volatile for a particular organization,
especially when CEO turnovers are happening. As narcissism is an innate characteristic, we
think our measure better captures CEO narcissism instead of corporate narcissism. We further
address this issue by including firm fixed effects in our analyses. Another issue of our measure isthat it may capture CEO style. Bamber et al. (2010) show that CEOs have their own style offinancial reporting, and their styles are associated with their demographic characteristics such as
education background, life, professional, and military experience. While it is not impossible that
our narcissism measure is associated with CEOs’ past experience and habits, they are distinct innature. Narcissism may be manifested by experience, but experience itself cannot foster
narcissism. We address this issue by including CEO fixed effects in our analyses. Table 7 reports
the results. After including firm fixed effects or CEO fixed effects, the association between our
narcissism measure and likelihood and frequency of issuing forecasts remains the significant andnegative. The significance does decrease, however. This suggests that our narcissism measure is
not explained by organizational ideal, and that the association between narcissism andmanagement forecast are not solely due to CEO styles.
Prior studies find that CFOs have significant influence on financial reporting (Ham et al.,2015; Jiang et al., 2010). It is possible that the relation between CEO narcissism andmanagement forecasts becomes weaker or even insignificant once CFO narcissism is included.
We examine this concern by including CFO narcissism and overconfidence in our analyses, andreports the estimation in table 8. In panel A, we re-estimate our previous models by replacing
CEO narcissism and overconfidence for CFO narcissism and overconfidence. We find that CFO
narcissism loads significantly and negatively for Issue and Freq, but insignificantly in forecast

22qualities. CFO overconfidence, however, loads significantly and positively for Issue and Freq,
negatively for Specificity, and positively for Miss, consistent with the findings for CEO
overconfidence in Hribar and Yang (2015). In panel B, we include both CEO and CEO
narcissism and overconfidence all at once. Our results for CEO narcissism still hold overall,
except for forecast Error. CFO narcissism, however, only loads significantly in Freq and Bias,and even that, its sign in Bias flips to negative, suggesting that CEO narcissism dominates CFO
narcissism in management forecast decisions. This is not surprising though. The CEO have themost power in a company, and a narcissistic CEO will overrule and exploit all other staff within
the company. It is also possible that narcissistic CEOs and narcissistic CFOs do not coexist in thesame company. One interesting observation is that CFO overconfidence consistently loads
significantly, in the direction opposite to CEO narcissism, consistent with the findings for CEO
overconfidence in Hribar and Yang (2015). This also confirms our notion that narcissism is adistinct construct from overconfidence.
Finally, there might be inconsistency in the databases of First Call CIG and I/B/E/S
Guidance Detail. We address this issue by re-conduct all our analyses for the First Call CIG data
only, and the results are reported in table 9. Consistent with our main findings, CEO narcissism
loads significantly in the likelihood and frequency of issuing forecasts, specificity, optimism, andaccuracy of forecasts, suggesting that our findings are not subject to data inconsistency issues.

5

Conclusion

This study investigates the association between CEO narcissism and management forecasting
practice. Distinct from economic incentives and constraints, narcissism, the personality trait,

23

plays a unique role in management forecasting decision. We measure CEO narcissism as theusage of first-person singular pronouns in conference calls and presentations, and find that CEO
narcissism is negatively associated with the likelihood and frequency of issuing forecasts,
negatively associated with forecast precision, and positively associated with forecast optimism
and accuracy. Our evidence is consistent with the view that narcissistic CEOs’ self-admirationand sense of superiority drives them to avoid possible unfavorable outcome, specifically missing
the forecast, at all costs, and therefore they are reluctant to issue forecasts, and only issue
forecasts when uncertainty is lower and accuracy is higher, and issue less precise forecasts.
Additional analyses show that it is CEO narcissism, not CFO narcissism, that plays a role inmanagement forecasting decisions.
Our paper contributes to our understanding of CEO decision making behavior anddeterminants of management forecasts. We show that psychological traits of CEOs play asignificant role in their decision making process which may not be well explained by economic
incentives. We also show that besides economic incentives and constraints, CEO narcissism is asignificant determinant of management forecasts.

24

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30

Appendix
Variable Definitions
Narcissism and Overconfidence Measures
Narci_CEO =CEO narcissism, the ratio of the number of first person singular pronouns
to the total number of first person singular plus plural pronouns in CEO’s
speeches in conference calls during the past three years.

Narci_CFO =CFO narcissism, the ratio of the number of first person singular pronouns
to the total number of first person singular plus plural pronouns in CFO’s
speeches in conference calls during the past three years.

OverConf =CEO overconfidence, defined as a dummy variable equal to one if the
CEO holds options despite a 67 percent increase in stock price (or more)
relative to striking price for at least twice, beginning in the first year the
CEO exhibits this behavior.

OverConf_CFO =CFO overconfidence, defined as a dummy variable equal to one if the
CFO holds options despite a 67 percent increase in stock price (or more)
relative to striking price for at least twice, beginning in the first year the
CFO exhibits this behavior.

Management Forecast Variables
Issue =

1 if firm makes at least one management earnings forecast during the
fiscal year t, and 0 otherwise.

Freq =

the number of management earnings forecasts made during the fiscal yeart.

Specificity =3 if the firm issued a point forecast during a fiscal period, 2 if an interval
forecast, 1 if an open-ended forecast, and 0 if a qualitative forecast.

Miss =

1 if actual earnings is less than the management forecast, and 0 otherwise.
For range forecasts, Miss = 1 if actual earnings is less than the lower
bound of the range estimate.

Bias =[(management forecast of EPS − actual EPS)/logged assets per share at
the beginning of the fiscal period]. If Bias > 0, the earnings forecast is
optimistically biased.

Error =

absolute value [(management forecast of earnings per share (EPS) −actual EPS)/ logged assets per share at the beginning of the fiscal period].
Accuracy of forecasts is the inverse of Error.

Horizon =number of days between the forecast date and the fiscal period-end date.

News =

Management forecast of EPS – analysts’ consensus forecast of EPS prior
to management forecast, scaled by logged assets per share.

31

Control Variables
logMV =BM =Natural log of the market value of the firm’s common equity (in$ million) at the beginning of the fiscal year t.
ratio of book value to market value of common equity at the beginning of
the fiscal year t.

ChgEarn =change of earnings, scaled by market cap at the beginning of the fiscal
year t.

EarnVol =standard deviation of annual earnings for the past 5 years.

Beta =

market beta, estimated using daily stock returns in year t.

Idiosync =idiosyncratic risk, standard errors of the residuals from the market model,using daily stock returns in year t.

CashComp =CEO’s cash compensation for the fiscal year t.

EquityComp =CEO’s equity compensation for the fiscal year t.

InstHolding =average percentage of institutional holdings in the fiscal year t.

OutDir =percentage of the board of directors that are not also officers of the firm
for year t, obtained from BoardEx.

NAF =number of analysts following the firm, before the fiscal year end for firms
without management earnings forecasts, before the last earnings forecast
for forecasting firms.

Disp =

analyst forecast dispersion for the fiscal year, standard deviation ofanalyst forecasts scaled by median analyst forecast. For forecasting firms,
this measure is calculated before the last earnings forecasts. For nonforecasting firms, this measure is calculated before the fiscal year end.

CEOTenure =Number of years CEO in position.

CEOHolding =Percentage of shares outstanding owned by the CEO in year t.

DAcc =

Discretionay accruals in year t, estimated from the modified Jones model.

Loss =

1 if the firm reports loss in year t, and 0 otherwise.

Litigate =1 if the firm belongs to the biotechnology (SIC codes 2833–2836), R&D
services (8731–8734), programming (7371–7379), computers (3570–
3577), electronics (3600–3674), or retailing (5200–5961) industry, and 0
otherwise.

Capx =

Capital expenditure in year t, scaled by total assets in year t-1.

R&D =R&D expenditures in year t, scaled by total assets in year t-1.

R&D_Dummy =1 if Compustat reports a missing R&D expenditure in year t, and 0
otherwise.

32

Table 1. Distribution of CEO Narcissism and Management Forecasts over Time
Year
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
Total

N
866
957
961
902
966
1105
1182
1168
1095
1042
1203
11447

Narci_CEO
0.191
0.194
0.200
0.199
0.197
0.188
0.188
0.188
0.190
0.196
0.197

OverConf
0.186
0.318
0.382
0.427
0.431
0.416
0.415
0.429
0.454
0.467
0.470

Issue
0.513
0.532
0.506
0.527
0.513
0.481
0.413
0.438
0.459
0.461
0.160

Freq
1.805
1.962
1.978
2.155
2.136
2.176
1.826
2.080
2.083
2.187
0.746

This table reports the distribution of CEO narcissism and management forecasts over time. Our
sample spans the period 2002 to 2013. Narci_CEO is CEO narcissism measured as the ratio of
the number of first person singular pronouns to the total number of first person singular plus
plural pronouns in CEO’s speeches in conference calls during the past three years. OverConf =CEO overconfidence, defined as a dummy variable equal to one if the CEO holds options despite
a 67 percent increase in stock price (or more) relative to striking price for at least twice,
beginning in the first year the CEO exhibits this behavior. See the appendix for other variable
definitions.

33

Table 2. Descriptive Statistics

Narci_CEO
Narci_CFO
OverConf
OverConf_CFO
Freq
Issue
Specificity
Miss
Bias
Error
Horizon
News
logMV
BM
ChgEarn
EarnVol
Beta
Idiosync
CashComp
EquityComp
InstHolding
OutDirNAF
Disp
CEOTenure
CEOHolding
DAcc
Loss
Litigate
Capx
R&D
R&D_Dummy

(1)
count
11447
7189
11447
11447
11447
11447
21976
21976
21886
21886
21976
21210
11447
11447
11447
11447
11447
11447
11447
11407
11447
11240
10456
10271
11447
11331
11447
11447
11447
11447
11447
11447

mean
0.193
0.159
0.405
0.201
1.904
0.447
2.055
0.311
-0.0480.107
196.407-0.039
7.593
0.567
0.183
0.059
1.205
2.135
1194.725
3197.586
0.752
0.789
15.048
0.067
7.224
1.632
0.001
0.169
0.323
0.052
0.035
0.405

sd
0.067
0.061
0.491
0.401
2.497
0.497
0.372
0.463
0.185
0.185
100.178
0.152
1.535
0.411
2.034
0.070
0.450
1.088
1983.313
5202.145
0.214
0.116
10.283
0.414
6.760
3.917
0.103
0.375
0.468
0.057
0.059
0.491

p25
0.145
0.115
0.000
0.000
0.000
0.000
2.000
0.000
-0.0570.013
103.000-0.0206.520
0.294-0.280
0.017
0.886
1.372
600.000
532.925
0.665
0.714
7.000
0.016
2.000
0.107
-0.026
0.000
0.000
0.017
0.000
0.000

p50
0.187
0.152
0.000
0.000
0.000
0.000
2.000
0.000
-0.0140.035
201.000-0.003
7.495
0.480
0.180
0.034
1.158
1.894
856.7311720.371
0.800
0.818
13.000
0.040
5.000
0.319
0.006
0.000
0.000
0.034
0.000
0.000

p75
0.235
0.195
1.000
0.000
4.000
1.000
2.000
1.000
0.011
0.100
290.000
0.008
8.569
0.750
0.640
0.073
1.471
2.597
1200.000
3961.705
0.898
0.889
21.0000.102
10.000
1.052
0.035
0.000
1.000
0.065
0.049
1.000

This table reports the descriptive statistics for our sample in the period 2002 to 2013. Narci_CEO
is CEO narcissism measured as the ratio of the number of first person singular pronouns to thetotal number of first person singular plus plural pronouns in CEO’s speeches in conference calls
during the past three years. OverConf = CEO overconfidence, defined as a dummy variable equal
to one if the CEO holds options despite a 67 percent increase in stock price (or more) relative tostriking price for at least twice, beginning in the first year the CEO exhibits this behavior. See theappendix for other variable definitions.

34

Table 3. Pearson Correlation

OverConf
Freq
Issue
Specificity
Miss
Bias
Error
HorizonNews

Narci_CEO-0.021(0.03)-0.075(0.00)-0.087(0.00)-0.013(0.06)
0.005(0.45)-0.011(0.10)-0.007(0.29)
0.01(0.15)-0.017(0.01)OverConf

0.05(0.00)
0.035(0.00)
0.017(0.01)-0.044(0.00)-0.069(0.00)
0.046(0.00)
0.004(0.54)-0.03(0.00)

This table reports the Pearson correlation between CEO narcissism and overconfidence andmanagement forecast variables. P-values are reported in parentheses below the correlation
coefficients. Our sample spans the period 2002 to 2013. Narci_CEO is CEO narcissism measured
as the ratio of the number of first person singular pronouns to the total number of first person
singular plus plural pronouns in CEO’s speeches in conference calls during the past three years.
OverConf = CEO overconfidence, defined as a dummy variable equal to one if the CEO holds
options despite a 67 percent increase in stock price (or more) relative to striking price for at least
twice, beginning in the first year the CEO exhibits this behavior. See the appendix for othervariable definitions.

35

Table 4. CEO Narcissism and the Tendency of Management Forecasts
Panel A. Logit Regression of the Probability of Management Forecast Issuance
Dependent variable = Issue
(1)
(2)
(3)
(4)
(5)
(6)
Narci_CEO-3.234***-3.227*** -3.204*** -3.828*** -3.755***(-5.05)(-5.06)(-4.93)(-5.63)(-5.45)
XEarn-0.390*(-1.65)
XGoodEarn-0.548***(-2.64)
XBadEarn-0.078(-0.45)
Narci_CEO * XEarn
2.020*(1.78)
Narci_CEO * XGoodEarn
2.411**(2.51)
Narci_CEO * XBadEarn
0.445(0.46)OverConf
0.075
0.068
0.059
0.056
0.056
(0.73)(0.68)(0.57)(0.54)(0.54)
CEOTenure-0.001-0.001-0.001(-0.10)(-0.12)(-0.12)
logCashComp
0.254*** 0.256*** 0.258***(4.24)(4.28)(4.28)****
logEquityComp
0.033
0.033
0.033**(2.24)(2.27)(2.26)
InstHolding
0.392
0.411
0.380
0.325
0.333
0.339
(1.16)(1.20)(1.12)(0.96)(0.99)(0.99)
OutDir
1.386*** 1.427*** 1.395*** 1.297*** 1.295*** 1.303***(2.90)(2.97)(2.93)(2.74)(2.72)(2.76)
***
***
***
***
***
logNAF
0.737
0.720
0.735
0.744
0.746
0.744***(2.76)(2.70)(2.74)(2.75)(2.75)(2.74)
logMV-0.116-0.134-0.117-0.197** -0.198** -0.195**(-1.22)(-1.41)(-1.22)(-2.02)(-2.00)(-1.96)BM-0.099-0.099-0.092-0.140-0.139-0.134(-0.89)(-0.86)(-0.81)(-1.25)(-1.25)(-1.22)
EarnVol-5.517*** -5.505*** -5.517*** -5.491*** -5.518*** -5.451***(-7.19)(-7.22)(-7.17)(-7.25)(-7.29)(-7.22)
Litigate-0.254-0.249-0.249-0.211-0.215-0.214(-1.15)(-1.13)(-1.12)(-0.95)(-0.96)(-0.96)
ChgEarn-0.053*** -0.052*** -0.052*** -0.054*** -0.054*** -0.043***(-4.96)(-4.63)(-4.90)(-5.08)(-5.25)(-3.20)Loss-0.619*** -0.628*** -0.619*** -0.586*** -0.585*** -0.578***(-6.26)(-6.26)(-6.28)(-5.58)(-5.22)(-5.42)
CEOHolding-0.021* -0.022** -0.021*-0.013-0.013-0.013(-1.91)(-1.99)(-1.92)(-1.12)(-1.13)(-1.12)
ROA
0.032
0.023
-0.033
0.198
0.200
0.212
(0.05)(0.04)(-0.05)(0.31)(0.32)(0.33)
Beta-0.524*** -0.512*** -0.526*** -0.542*** -0.544*** -0.542***36

Idiosync
Pseudo.R2
N(-4.49)(-4.33)(-4.52)(-4.65)(-4.68)(-4.69)-0.204*** -0.195*** -0.206*** -0.211*** -0.209*** -0.207***(-3.13)(-3.00)(-3.15)(-3.26)(-3.17)(-3.12)0.23990.23450.24000.2433
0.244
0.244
11104
11104
11104
11068
11068
11068

37

Panel B. Linear Regression of Frequency of Management Forecasts
Dependent variable = Freq
(1)
(2)
(3)
(4)
(5)
(6)
Narci_CEO-2.835***-2.819*** -2.715*** -3.453*** -3.451***(-5.00)(-4.99)(-4.80)(-5.60)(-5.28)XEarn-0.538***(-2.83)
XGoodEarn-0.542**(-2.52)
XBadEarn-0.397***(-3.57)
Narci_CEO * XEarn
2.223**(2.47)
Narci_CEO * XGoodEarn
2.245**(2.20)
Narci_CEO * XBadEarn
1.423**(2.02)OverConf
0.101
0.092
0.104
0.102
0.101
(1.11)(1.03)(1.12)(1.10)(1.09)
CEOTenure-0.008-0.008-0.008(-1.30)(-1.32)(-1.32)
logCashComp
0.181*** 0.186*** 0.185***(3.41)(3.47)(3.45)
logEquityComp
0.034**
0.034**
0.034**(2.50)(2.52)(2.52)
InstHolding
0.314
0.320
0.297
0.244
0.273
0.279
(1.33)(1.31)(1.24)(1.03)(1.16)(1.16)
OutDir
1.251*** 1.298*** 1.258*** 1.154*** 1.157*** 1.153***(3.27)(3.32)(3.29)(3.07)(3.10)(3.09)
logNAF
0.487*** 0.476*** 0.484*** 0.487*** 0.484*** 0.484***(3.63)(3.50)(3.57)(3.59)(3.55)(3.55)
logMV
0.110
0.094
0.109
0.043
0.049
0.049
(1.56)(1.31)(1.53)(0.63)(0.71)(0.72)
BM-0.138-0.136-0.129-0.161*-0.142-0.141(-1.58)(-1.53)(-1.48)(-1.85)(-1.62)(-1.63)
EarnVol-3.827*** -3.820*** -3.827*** -3.825*** -3.699*** -3.675***(-6.29)(-6.44)(-6.26)(-6.21)(-6.25)(-6.25)*******
Litigate-0.378-0.379-0.372-0.341-0.352-0.351*(-1.98)(-2.00)(-1.94)(-1.78)(-1.84)(-1.83)
ChgEarn-0.012-0.010-0.010-0.012-0.009-0.011(-0.91)(-0.77)(-0.79)(-0.90)(-0.72)(-0.90)Loss-0.498*** -0.508*** -0.497*** -0.479*** -0.448*** -0.451***(-4.38)(-4.34)(-4.41)(-4.27)(-3.94)(-4.07)
CEOHolding-0.017-0.018-0.017-0.005-0.004-0.004(-1.48)(-1.58)(-1.50)(-0.37)(-0.36)(-0.36)
ROA-0.615-0.658-0.692-0.536-0.558-0.572(-1.04)(-1.14)(-1.21)(-0.95)(-0.99)(-1.00)Beta-0.522*** -0.513*** -0.523*** -0.533*** -0.533*** -0.534***(-6.09)(-5.88)(-6.10)(-6.06)(-6.15)(-6.17)
Idiosync-0.090*-0.085*-0.092* -0.097** -0.092*-0.092*38

Adj.R2N(-1.89)
0.260
11127

(-1.76)
0.255
11127

(-1.93)
0.260
11127

(-2.07)
0.263
11091

(-1.93)
0.264
11091

(-1.93)
0.264
11091

This table reports the impact of CEO narcissism on the tendency of management forecasts. PanelA reports results from a logit regression of forecast issuance dummies on CEO narcissism andoverconfidence, and panel B reports results from a linear regression of management forecast
frequencies. Issue = 1 if firm makes at least one management earnings forecast during the fiscal
year t, and 0 otherwise. Freq = the number of management earnings forecasts made during the
fiscal year t. Narci_CEO is CEO narcissism measured as the ratio of the number of first person
singular pronouns to the total number of first person singular plus plural pronouns in CEO’s
speeches in conference calls during the past three years. OverConf = CEO overconfidence,
defined as a dummy variable equal to one if the CEO holds options despite a 67 percent increasein stock price (or more) relative to striking price for at least twice, beginning in the first year the
CEO exhibits this behavior. See the appendix for other variable definitions. Industry and year
fixed effects are included but not tabulated. T-statistics are calculated based on standard errors
clustered by firm and year, and reported in parenthese. *, **, and *** indicate 1%, 5%, and 10%
significance levels, respectively.

39

Table 5. Ordered Logit Regression of Forecast Specificity

Narci_CEO
OverConf
CEOTenure
logCashComp
logEquityComp
InstHolding
OutDirlogNAF
logMV
BMEarnVol
Litigate
ChgEarn
Loss
CEOHolding
ROA
Beta
Idiosync
DAcc
News
logHorizon
Pseudo.R2
N

Dependent variable = Specificity
(2)
(3)
(4)
-1.204**-1.256**(-1.99)(-2.07)-0.025-0.021-0.023(-0.19)(-0.16)(-0.16)0.001(0.08)
0.102(1.15)-0.018(-0.93)0.756*
0.773*
0.766*
0.763*(1.79)(1.89)(1.88)(1.93)-1.601***-1.625***-1.606***-1.575***(-2.72)(-2.69)(-2.70)(-2.60)
0.187
0.201
0.189
0.194
(1.34)(1.44)(1.36)(1.37)
0.100
0.087
0.100
0.087
(1.63)(1.47)(1.63)(1.19)-0.165-0.183-0.167-0.182(-0.75)(-0.83)(-0.76)(-0.80)
1.477
1.449
1.481
1.582
(1.24)(1.20)(1.24)(1.34)
0.196
0.213
0.194
0.190
(0.70)(0.75)(0.67)(0.67)-0.023-0.024-0.023-0.025(-0.54)(-0.58)(-0.56)(-0.62)
0.012
0.016
0.011
-0.006(0.04)(0.06)(0.04)(-0.02)
0.008
0.008
0.008
0.006
(0.30)(0.30)(0.30)(0.21)-0.311-0.227-0.285-0.323(-0.23)(-0.17)(-0.21)(-0.24)0.402**
0.399**
0.403**
0.393**(2.52)(2.46)(2.52)(2.44)
0.048
0.049
0.048
0.045
(0.67)(0.70)(0.67)(0.62)
0.697
0.752
0.691
0.656
(1.39)(1.56)(1.43)(1.41)
0.428
0.430
0.426
0.435
(1.13)(1.16)(1.12)(1.13)-0.294***-0.294***-0.294***-0.294***(-6.39)(-6.41)(-6.40)(-6.38)
0.036
0.035
0.036
0.036
20691
20694
20691
20635
(1)
-1.206**(-1.99)40

This table reports results from a ordered logit regression of management forecast precision,
measured as Specificity, which = 3 if the firm issued a point forecast during a fiscal period, 2 if aninterval forecast, 1 if an open-ended forecast, and 0 if a qualitative forecast. Narci_CEO is CEO
narcissism measured as the ratio of the number of first person singular pronouns to the total
number of first person singular plus plural pronouns in CEO’s speeches in conference calls during
the past three years. OverConf = CEO overconfidence, defined as a dummy variable equal to one
if the CEO holds options despite a 67 percent increase in stock price (or more) relative to striking
price for at least twice, beginning in the first year the CEO exhibits this behavior. See theappendix for other variable definitions. Industry and year fixed effects are included but not
tabulated. T-statistics are calculated based on standard errors clustered by firm and year, andreported in parentheses. *, **, and *** indicate 1%, 5%, and 10% significance levels, respectively.

41

Table 6. Regression of Forecast Bias and Error on CEO Narcissism

Narci_CEO
OverConf
CEOTenure
logCashComp
logEquityComp
InstHolding
OutDirlogNAF
logMV
BMEarnVol
Litigate
ChgEarn
Loss
CEOHolding
ROA
Beta
Idiosync
DAcc
News
logHorizon
Adj.R2N(1)Miss
1.065**(2.06)-0.132*(-1.75)0.007(1.15)-0.318***(-2.81)-0.012(-0.85)-0.323(-1.57)0.223(0.63)
0.438***(4.80)-0.149**(-2.46)
1.187***(7.97)-0.532(-0.51)-0.063(-0.44)-0.304***(-6.67)0.180(1.12)-0.027**(-2.45)-3.661***(-4.03)-0.100(-0.81)0.104(1.52)
1.768***(3.01)
3.858***(13.05)0.470***(11.05)
0.160
20626

(2)
Bias
0.022
(1.13)-0.004(-1.13)0.000(0.74)-0.017***(-2.90)0.000(0.15)-0.020(-1.59)-0.004(-0.21)0.026***(5.24)-0.005*(-1.82)0.058***(5.54)
0.034(0.64)-0.007(-1.07)-0.023***(-9.15)0.013(1.23)-0.001*(-1.65)-0.367***(-6.38)-0.020***(-3.04)0.007**(2.05)
0.088***(2.97)
0.849***(40.62)0.001(0.36)
0.660
20635

42

(3)
Error
-0.049**(-2.34)0.006(1.20)-0.000(-1.53)0.019***(2.64)-0.001(-0.69)0.012(0.96)
0.056***(3.05)-0.007(-1.00)0.008**(2.11)
0.025**(2.32)
0.070(1.36)-0.014***(-2.90)-0.003(-1.04)0.087***(6.18)
0.001(0.98)
0.241***(4.66)
0.019***(2.78)
0.030***(5.66)-0.024(-0.74)-0.802***(-24.84)
0.031***(19.15)
0.510
20635

Column (1) reports results from a logit regression of Miss, an indicator of optimistic forecasts, on
CEO narcissism, column (2) reports results from a linear regression of forecast bias, and column(3) reports results from a linear regression of forecast error. Miss = 1 if actual earnings is less thanthe management forecast, and 0 otherwise. For range forecasts, Miss = 1 if actual earnings is lessthan the lower bound of the range estimate. Bias = [(management forecast of EPS − actual
EPS)/logged assets per share at the beginning of the fiscal period]. If Bias > 0, the earnings
forecast is optimistically biased. Error = absolute value [(management forecast of earnings per
share (EPS) − actual EPS)/ logged assets per share at the beginning of the fiscal period].
Accuracy of forecasts is the inverse of Error. Narci_CEO is CEO narcissism measured as theratio of the number of first person singular pronouns to the total number of first person singularplus plural pronouns in CEO’s speeches in conference calls during the past three years. OverConf= CEO overconfidence, defined as a dummy variable equal to one if the CEO holds options
despite a 67 percent increase in stock price (or more) relative to striking price for at least twice,
beginning in the first year the CEO exhibits this behavior. See the appendix for other variable
definitions. Industry and year fixed effects are included but not tabulated. T-statistics arecalculated based on standard errors clustered by firm and year, and reported in parentheses. *, **,and *** indicate 1%, 5%, and 10% significance levels, respectively.

43

Table 7. Firm Fixed Effects and Executive Fixed Effects

Narci_CEO
OverConf
CEOTenure
logCashComp
logEquityComp
InstHolding
OutDirlogNAF
logMV
BMEarnVol
ChgEarn
Loss
CEOHolding
ROA
Beta
Idiosync
Adj.R2N

Firm-fixed Effects
(1)
(2)
Issue
Freq
-2.331**-0.723*(-2.25)(-1.96)-0.0170.086(-0.12)(1.63)
0.018
0.001(1.56)(0.35)
0.140-0.008(1.31)(-0.20)-0.010-0.004(-0.53)(-0.60)0.727-0.030(1.50)(-0.18)0.346
0.114(0.54)(0.45)
1.525***
0.638***(14.75)(22.48)-0.0690.086*(-0.56)(1.88)
0.055
0.016(0.30)(0.23)-3.554***-1.806***(-3.23)(-4.52)-0.077***-0.015*(-3.44)(-1.86)0.053-0.116*(0.31)(-1.81)-0.0130.003(-0.45)(0.37)
3.761***
1.030***(4.62)(3.38)-0.091-0.078(-0.65)(-1.52)-0.075-0.047*(-0.98)(-1.69)
0.341
0.672
5690
11091

CEO-fixed Effects
(3)
(4)
Issue
Freq
-3.966**-1.621***(-2.56)(-3.32)0.118
0.098(0.56)(1.46)-0.0280.036*(-0.49)(1.67)
0.285**
0.031(2.16)(0.67)-0.020-0.001(-0.94)(-0.15)0.855
0.110(1.52)(0.64)-0.3830.183(-0.52)(0.65)
1.519***
0.620***(12.35)(20.82)-0.244*-0.015(-1.68)(-0.30)-0.173-0.078(-0.79)(-1.04)-3.682***-1.748***(-2.77)(-3.99)-0.081***-0.012(-3.20)(-1.42)0.182-0.022(0.95)(-0.33)-0.0340.009(-0.88)(0.81)
4.773***
1.326***(5.10)(4.21)-0.096-0.165***(-0.60)(-3.08)-0.065-0.036(-0.76)(-1.24)
0.324
0.705
4155
11091

This table reports the results for management forecast issuance and frequency, incorporating firm
fixed effects and CEO fixed effects. Issue = 1 if firm makes at least one management earnings
forecast during the fiscal year t, and 0 otherwise. Freq = the number of management earnings
forecasts made during the fiscal year t. Narci_CEO is CEO narcissism measured as the ratio of
the number of first person singular pronouns to the total number of first person singular plus
plural pronouns in CEO’s speeches in conference calls during the past three years. OverConf =CEO overconfidence, defined as a dummy variable equal to one if the CEO holds options despite
a 67 percent increase in stock price (or more) relative to striking price for at least twice,44

beginning in the first year the CEO exhibits this behavior. See the appendix for other variable
definitions. Year fixed effects are included but not tabulated. T-statistics are calculated based onstandard errors clustered by firm and year, and reported in parentheses. *, **, and *** indicate 1%,5%, and 10% significance levels, respectively.

45

Table 8. The Impact of CFO Narcissism on Management Forecasts
Panel A. CFO narcissism alone

Narci_CFO
OverConf_CFO
Insider
InstHolding
OutDirlogNAF
logMV
BMEarnVol
Litigate
ChgEarn
Loss
ROA
Beta
Idiosync(1)Issue-1.698**(-2.41)0.357***(2.79)-0.017(-1.45)0.052(0.13)
1.961***(2.68)
0.902***(2.78)-0.209*(-1.77)-0.084(-0.65)-6.112***(-7.53)-0.400(-0.82)-0.046**(-2.46)-0.577***(-4.22)-0.071(-0.10)-0.597***(-4.61)-0.247**(-2.48)(2)Freq-1.843***(-3.58)0.313***(2.89)-0.005(-0.52)0.196(0.62)
1.851***(2.90)
0.543***(3.40)
0.073(0.84)-0.154(-1.34)-4.503***(-7.60)-0.498*(-1.81)0.004(0.21)-0.433***(-2.76)-0.705(-1.20)-0.654***(-4.71)-0.100(-1.26)

0.267
7061

0.282
7106

DAcc
News
logHorizon
Adj.R2N(3)
Specificity
0.256(0.37)-0.218***(-3.43)0.010*(1.79)
0.535**(2.45)-1.559***(-4.95)0.097(0.89)
0.113**(2.51)-0.494***(-3.13)0.696(0.82)-0.046(-0.22)0.027(0.81)
0.236(1.09)-1.448(-1.42)0.351**(2.47)
0.121**(2.20)
1.254***(3.05)
0.437(1.56)-0.284***(-6.75)
0.040
13292

46

(4)
Miss
-0.097(-0.28)0.154***(3.15)-0.016***(-3.09)-0.801***(-6.19)0.342(0.96)
0.419***(6.77)-0.219***(-5.67)1.033***(12.79)-1.933**(-2.16)-0.038(-0.38)-0.313***(-8.39)0.390***(3.89)-1.668***(-2.75)-0.028(-0.26)0.133***(2.94)
1.762***(3.42)
3.550***(8.91)
0.496***(8.69)
0.154
13276

(5)
Bias
-0.025(-1.44)-0.002(-0.92)-0.000(-0.90)-0.031***(-5.50)-0.002(-0.24)0.021***(5.59)-0.006***(-2.93)0.050***(6.93)-0.027(-0.83)0.000(0.10)-0.021***(-11.09)
0.023***(4.34)-0.273***(-8.54)-0.017***(-3.14)0.011***(3.65)
0.082***(4.13)
0.841***(31.16)0.001(0.28)
0.621
13292

(6)
Error
-0.023(-0.59)-0.004(-0.91)-0.000(-0.78)0.009(0.47)
0.061*(1.86)-0.006(-1.17)0.009**(2.51)
0.023**(2.04)
0.129*(1.81)
0.008(0.80)-0.004*(-1.68)0.071***(4.45)
0.184***(2.88)-0.009(-0.85)0.030***(4.64)-0.004(-0.14)-0.773***(-17.11)0.032***(8.99)
0.490
13292

Panel B. CEO and CFO narcissism when included together

Narci_CEO
OverConf
Narci_CFO
OverConf_CFO
Insider
InstHolding
OutDirlogNAF
logMV
BMEarnVol
Litigate
ChgEarn
Loss
ROA
Beta
Idiosync(1)Issue-2.527**(-2.31)-0.087(-0.66)-0.914(-1.22)0.387***(3.26)-0.016(-1.43)0.055(0.13)
1.893***(2.59)
0.921***(2.86)-0.193(-1.62)-0.074(-0.55)-6.059***(-7.41)-0.405(-0.86)-0.046**(-2.50)-0.561***(-4.17)-0.054(-0.07)-0.607***(-4.70)-0.250**(-2.53)(2)
Freq-1.916**(-2.06)-0.023(-0.24)-1.238**(-2.49)0.317***(3.20)-0.005(-0.48)0.201(0.64)
1.802***(2.83)
0.550***(3.49)
0.086(0.97)-0.149(-1.29)-4.488***(-7.58)-0.489*(-1.87)0.004(0.21)-0.422***(-2.74)-0.710(-1.21)-0.663***(-4.73)-0.100(-1.26)

0.270
7061

0.284
7106

DAcc
News
logHorizon
Adj.R2N(3)
Specificity-1.506**(-2.48)-0.184**(-2.07)0.837(1.10)-0.142*(-1.92)0.011*(1.85)
0.622***(2.85)-1.543***(-4.79)0.113(1.03)
0.129***(2.80)-0.471***(-2.98)0.854(0.99)-0.085(-0.40)0.027(0.83)
0.251(1.15)-1.309(-1.26)
0.356**(2.50)
0.129**(2.29)
1.175***(2.89)
0.429(1.54)-0.284***(-6.76)
0.042
13292

47

(4)
Miss
0.741**(2.43)-0.125**(-2.46)-0.346(-0.93)0.204***(4.58)-0.017***(-3.23)-0.756***(-6.07)0.324(0.92)
0.433***(7.04)-0.229***(-5.66)1.008***(11.92)-1.951**(-2.18)-0.040(-0.40)-0.313***(-8.39)0.388***(3.88)-1.577***(-2.61)-0.031(-0.28)0.139***(3.10)
1.760***(3.36)
3.554***(8.96)
0.496***(8.70)
0.155
13276

(5)
Bias
0.029***(2.78)-0.001(-0.38)-0.035*(-1.98)-0.001(-0.68)-0.000(-0.97)-0.030***(-4.94)-0.003(-0.33)0.021***(5.79)-0.006***(-3.12)0.049***(6.73)-0.028(-0.87)0.001(0.17)-0.021***(-11.15)
0.023***(4.31)-0.271***(-8.23)-0.017***(-3.16)0.011***(3.67)
0.082***(4.09)
0.841***(31.38)0.001(0.28)
0.621
13292

(6)
Error
-0.021(-0.72)0.009**(2.21)-0.017(-0.44)-0.007(-1.56)-0.000(-0.73)0.005(0.26)
0.062*(1.91)-0.007(-1.41)0.009***(2.64)
0.024**(2.13)
0.126*(1.79)
0.009(0.85)-0.004*(-1.67)0.071***(4.48)
0.176***(2.75)-0.009(-0.85)0.030***(4.53)-0.003(-0.10)-0.773***(-16.96)0.032***(9.04)
0.490
13292

This table reports the impact of CFO narcissism on management forecasts. In panel A, only CFO
narcissism and overconfidence are included, and in panel B, both CEO and CFO narcissism areincluded. Specificity = 3 if the firm issued a point forecast during a fiscal period, 2 if an interval
forecast, 1 if an open-ended forecast, and 0 if a qualitative forecast. Miss = 1 if actual earnings isless than the management forecast, and 0 otherwise. For range forecasts, Miss = 1 if actual
earnings is less than the lower bound of the range estimate. Bias = [(management forecast of EPS− actual EPS)/logged assets per share at the beginning of the fiscal period]. If Bias > 0, theearnings forecast is optimistically biased. Error = absolute value [(management forecast of
earnings per share (EPS) − actual EPS)/ logged assets per share at the beginning of the fiscal
period]. Accuracy of forecasts is the inverse of Error. Narci_CEO is CEO narcissism measured
as the ratio of the number of first person singular pronouns to the total number of first person
singular plus plural pronouns in CEO’s speeches in conference calls during the past three years.
OverConf = CEO overconfidence, defined as a dummy variable equal to one if the CEO holds
options despite a 67 percent increase in stock price (or more) relative to striking price for at least
twice, beginning in the first year the CEO exhibits this behavior. See the appendix for othervariable definitions. Industry and year fixed effects are included but not tabulated. T-statistics arecalculated based on standard errors clustered by firm and year, and reported in parentheses. *, **,and *** indicate 1%, 5%, and 10% significance levels, respectively.

48

Table 9. Robustness Check: Only Management Forecasts from First Call Data

Narci_CEO
OverConf
CEOTenure
logCashComp
logEquityComp
InstHolding
OutDirlogNAF
logMV
BMEarnVol
ChgEarn
Loss
CEOHolding
ROA
Beta
Idiosync
Litigate
Adj.R2N(1)
Issue-4.021***(-6.27)0.120(1.21)-0.001(-0.19)0.244***(4.07)
0.031**(2.03)
0.717**(2.36)
1.082**(2.33)
0.303***(2.86)-0.040(-0.69)-0.048(-0.41)-4.355***(-5.13)-0.061***(-4.12)-0.753***(-7.29)-0.010(-0.80)-0.227(-0.37)-0.503***(-3.64)-0.169***(-3.04)-0.096(-0.45)
0.239
7797

(2)
Freq
-2.898***(-5.63)0.124*(1.65)-0.009*(-1.88)0.173***(3.94)
0.026**(2.12)
0.328**(2.13)
0.751**(2.15)
0.193***(4.69)
0.077(1.62)-0.059(-0.83)-2.739***(-4.39)-0.020(-1.57)-0.441***(-3.62)-0.001(-0.08)-0.408(-0.92)-0.400***(-3.54)-0.103***(-2.77)-0.202(-1.19)
0.286
9363

(3)
Specificity-1.905***(-3.09)-0.083(-0.93)-0.001(-0.15)0.104(1.30)-0.017(-1.49)0.526**(2.48)-1.396***(-4.28)0.211***(2.72)
0.082*(1.75)
0.090(0.58)
1.576***(2.76)
0.097(0.61)-0.069*(-1.93)-0.075(-0.37)0.002(0.22)
1.517(1.52)
0.435***(4.85)
0.081(1.33)
0.033
12836

(5)
Miss
1.098*(1.80)-0.177***(-2.61)0.017**(2.34)-0.347***(-3.33)-0.012(-0.68)-0.242(-0.85)0.280(0.55)
0.390***(2.98)-0.153***(-3.41)1.100***(6.42)-0.526(-0.66)-0.277(-1.55)-0.303***(-6.84)0.087(0.45)-0.045***(-2.96)-2.740***(-2.76)-0.066(-0.56)0.034(0.61)
0.129
13510

(5)
Bias
0.053***(3.93)
0.001(0.35)
0.000(1.50)-0.011**(-2.15)0.001(1.47)-0.014*(-1.87)-0.028**(-2.57)0.024***(7.84)-0.007***(-4.49)0.048***(7.06)-0.024(-0.66)-0.013**(-2.68)-0.021***(-9.58)0.019***(3.11)-0.004***(-5.02)-0.253***(-7.65)-0.023***(-5.62)0.011***(4.63)
0.222
12757

(6)
Error
-0.060*(-1.68)0.003(0.58)
0.000(0.47)
0.007(1.32)
0.001(0.76)-0.001(-0.05)0.067*(1.69)
0.001(0.15)
0.005(1.47)
0.055***(2.99)
0.194**(2.28)-0.002(-0.34)-0.012***(-3.00)0.075***(5.91)
0.003(1.04)
0.121(1.59)
0.007(0.65)
0.025***(4.71)
0.158
12757

This table reports the results when only management forecasts reported in Firscal Call CIG
database are included in our analyses. Issue = 1 if firm makes at least one management earnings
forecast during the fiscal year t, and 0 otherwise. Freq = the number of management earnings
forecasts made during the fiscal year t. Specificity = 3 if the firm issued a point forecast during afiscal period, 2 if an interval forecast, 1 if an open-ended forecast, and 0 if a qualitative forecast.
Miss = 1 if actual earnings is less than the management forecast, and 0 otherwise. For range
forecasts, Miss = 1 if actual earnings is less than the lower bound of the range estimate. Bias =49

[(management forecast of EPS − actual EPS)/logged assets per share at the beginning of the fiscal
period]. If Bias > 0, the earnings forecast is optimistically biased. Error = absolute value[(management forecast of earnings per share (EPS) − actual EPS)/ logged assets per share at the
beginning of the fiscal period]. Accuracy of forecasts is the inverse of Error. Narci_CEO is CEO
narcissism measured as the ratio of the number of first person singular pronouns to the total
number of first person singular plus plural pronouns in CEO’s speeches in conference calls during
the past three years. OverConf = CEO overconfidence, defined as a dummy variable equal to one
if the CEO holds options despite a 67 percent increase in stock price (or more) relative to striking
price for at least twice, beginning in the first year the CEO exhibits this behavior. See theappendix for other variable definitions. Industry and year fixed effects are included but not
tabulated. T-statistics are calculated based on standard errors clustered by firm and year, andreported in parentheses. *, **, and *** indicate 1%, 5%, and 10% significance levels, respectively.

50