Professor Aloke (Al) Ghosh spoke at the HEC Business School, Switzerland in 2010. During this presentation, Professor Ghosh discusses managerial exposure to losses.

1. Managerial Exposure to Losses
Aloke (Al) Ghosh
Stan Ross Department of Accountancy
Baruch College, The City University of New York
Box B12-225, One Bernard Baruch Way
New York, NY 10010
e-mail: Aloke.Ghosh@baruch.cuny.edu
and
Doocheol Moon
School of Business
Yonsei University
Seoul, Korea
e-mail: dmoon@yonsei.ac.kr
November 2010

2. Managerial Exposure to Losses
1. Introduction
In a recent study, Roychowdhury (2006) provides persuasive evidence consistent with the premise that managers manipulate operating (‘real’) activities to avoid reporting losses. By deviating from normal operations, managers avoid reporting losses through cash flow from operations. Similarly, the discontinuity in the frequency of firm-years around zero earnings (e.g., Hayn 1995, Burgstahler and Dichev 1997) is widely cited as evidence of earnings management to avoid reporting losses.1 In a related survey, Graham et al. (2005) conclude that executives prefer not to report losses by manipulating earnings even when such activities might erode firm value. But why are Chief Executive Officers (CEOs) so keen to avoid reporting losses?
Some popular explanations for earnings management include bonus compensation and capital market consequences (e.g., Hayn 1995, Dechow and Sloan 1991). However, changes in bonus compensation are unlikely to be large because managers report small profits rather than losses. Similarly, because stock market response to losses is muted (e.g., Joos and Plesko 2005, Hayn 1995), managers are unlikely to be concerned about capital market penalties from reporting losses. In this study, we investigate an alternative explanation that is more directly associated with the CEO’s personal exposure to losses, job security. In particular, we examine whether losses lead to higher CEO turnover.
The decision to replace a CEO is probably one of the most important decisions made by the board of directors with long-term implications for a firms’ investment, operating and financing decisions (Huson et al. 2001). CEO turnover was around 10% per year during the 1970s and 1980s and 11% in the 1990s (Murphy and Zabonjik 2004). However, between 1992 and 2005, annual CEO turnover jumped to 15%. In the more recent years since 1998, CEO turnover is
1The claims of earnings management based on observed discontinuities in firm-year distributions are controversial. For instance, Durtschi and Easton (2005) attribute the discontinuities in firm-year distributions to deflation and sample selection criteria. Similarly, Dechow et al. (2003) are unable to document evidence consistent with firms using accounting accruals to report small profits. 2

3. around 16.5% implying that the average CEO tenure is just over six years (Kaplan and Minton 2006). More important, while prior studies find modest relationship between turnover and firm performance (Murphy 1999, Murphy and Zimmerman 1993), Kaplan and Minton (2006) find that the CEO turnover-performance relationship is much stronger for the recent years which suggests that boards have become more sensitive to firm performance and are acting decisively in response to poor performance. Overall, the results suggest that the CEO’s job is more precarious than thought previously.
Prior studies examining the relationship between CEO turnover and firm performance tend to use either accounting measures (e.g., operating income, income from continuing operations, net income) or/and stock price measures (e.g., stock returns, industry adjusted stock returns) of performance. Our fundamental hypothesis is that losses capture an independent assessment of the CEO’s ability that is not fully captured in the traditional accounting and market-based performance measures. In addition to reflecting poor or declining performance, losses are one of the ultimate indicators of management failure. Therefore, boards are more likely to closely scrutinize CEO tenure considerations for loss firms. Boards might also be concerned that their reputation as the ultimate monitors of management might be tarnished if they do not hold CEOs accountable for losses, which erodes shareholder equity. Finally, because annual losses frequently trigger concurrent and future dividend omissions and reductions (DeAngelo et al. 1992), which are important shareholder considerations, it might be easier for boards to justify firing a CEO when firms report losses.
Based on a comprehensive sample of CEO turnovers between 1997 and 2005, we find a statistically and economically significant relationship between CEO turnover and accounting losses. Controlling for the other determinants of CEO turnover including market and accounting measures of performance, volatility, industry concentration, firm size, growth, restructuring activities, financial restatements, and CEO age, we find that CEOs reporting losses are more likely to lose their jobs within the two-year period following losses, including the year of the loss, 3

4. compared to profit firms. The economic magnitude of the estimates is also large. Holding the other variables at the mean values, we find that the probability of a CEO losing a job within two years of reporting a loss is about 52% higher than firms reporting profits. Additionally, our results suggest that boards typically tend to focus on the bottom line number; CEOs are held accountable for losses when a loss includes core, non-core, and discontinued operations and not just core operations.
Prior studies document that sustained earnings growth is rewarded by debt and equity markets because of better performance and superior managerial ability (Elliott et al. 2010, Ghosh et al. 2005, Barth et al. 1999). Similar to the studies examining the rewards from sustained growth for positive earnings, we analyze whether sustained losses impact CEO turnover by including five indicator variables measuring consecutive annual losses from years one to five. We observe that the relationship between CEO turnover and losses is the strongest when a firm reports a loss for the current year. Controlling for the current period loss, CEOs are more likely to be dismissed when a firm reports two consecutive annual losses. However, losses sustained over three or more years do not increase the chances of a CEO turnover. These results suggest that boards play a proactive role in holding management responsible for poor performance and that they do not allow matters to worsen before firing the incumbent CEO.
Our analyses assume that accounting loss is a pre-determined variable. However, because prior research suggests that accounting loss might be endogenously determined (Klein and Marquardt 2006, Joos and Plesko 2005), the regression estimates from a logistic regression of CEO turnover on an indicator variable for accounting losses might be biased and inconsistent. We overcome the endogeneity problem using a two-stage least squares estimation procedure. Drawing on prior studies, in the first stage we model the likelihood of a firm reporting an annual loss. In the second stage, we use the estimated value of the likelihood of a loss as an instrumental variable in the CEO turnover regressions. After controlling for endogeneity of
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5. accounting losses, we continue to find unusually high frequency of CEO turnover for firms reporting losses.
Prior studies find that the stock market views the appointment of an outsider CEO more favorably than the appointment of an insider CEO, especially when the incumbent CEO is forced to resign because of performance related reasons (e.g., Borokhovich et al. 1996). Therefore, we also examine whether losses increase the likelihood that the board hires an outsider to replace the incumbent CEO to send a credible signal to investors. We find that losses lead to more frequent appointments of CEOs from outside the firm.
The rest of the paper is organized as follows. Section 2 develops the hypotheses, Section 3 outlines our research design to test our hypotheses, and Section 4 describes the sample selection procedure and the data. Section 5 reports the empirical results, Section 6 discusses sensitivity analyses, and finally Section 7 concludes the paper.
2. Hypothesis Development
Annual reports, news releases and press coverages often reference the importance of consistently making profits which suggests that management has incentives to avoid reporting losses. In a survey and interview of 400 key executives directly involved in the financial reporting process, Graham et al. (2005) find that 65% of the executives prefer to report a profit rather than a loss. Consistent with the loss-avoidance conjecture, Burgstahler and Dichev (1997) find evidence of earnings management to avoid reporting losses.2 In a subsequent study, Roychowdhury (2006) provides direct evidence of management using real activities to avoid reporting los
2Earnings management could include a broad range of actions that affect earnings through operating, investing and financing decisions or through pure accounting choices. Roychowdhury (2006) finds that firms avoid losses by offering price discounts to temporarily increase sales, by increasing production temporarily to decrease the cost of goods sold, and by reducing discretionary expenditures aggressively to improve operating margins. 5

6. Why are CEOs so concerned about reporting accounting losses and why would they go to such lengths to manage earnings so as not to report losses? In the subsequent sub-section, we hypothesize that the primary reason for CEOs avoiding losses is related to career concerns. Anecdotal evidence supports this conjecture. For example, Jacques Aigrain, the CEO of Swiss Re, was dismissed following the announcement of an annual loss in 2009.
Losses and Career Concerns
Management in publicly held corporations is entrusted with the task of running a business to generate profits for shareholders. Graham et al. (2005) find that three-fourths of the survey respondents believe that their inability to avoid losses is seen as a “managerial failure” by the executive labor market and by corporate boards. According to one of the surveyed executives, “if I miss the target, I am out of a job.” One such target includes avoiding losses; failure to report a profit may be seen as a sign of an incompetent executive. Similarly, Watts (2003) claims that “managers have incentives to hide losses to avoid being fired before their tenure is over” because admitting to losses could indicate that they invested in negative net present value projects.
The board of directors is primarily charged with the responsibility of monitoring, evaluating, and rewarding management and ultimately firing a CEO for poor performance. Board members asses the ability of the CEO based on reported numbers and inside information. When a firm reports a loss rather than a profit, it acts as a heuristic for ultimate failure (Pinnuck and Lillis 2007). Accounting losses are a signal that the underlying business model has failed under the present leadership.
When firms report losses, the board is expected to become more proactive in finding out the reasons for losses and ultimately taking the decision to dismiss the CEO for several reasons. First, shareholders might expect the board to dismiss the CEO when a firm reports a loss because of erosion in equity value and the board might be acting to placate shareholders (Watts 2003). Second, boards have no assurance that CEOs would change their business
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7. strategy following losses, which suggests that current losses might persist into the future. For instance, instead of abandoning loss-making projects, CEOs may continue to operate their pet projects by subsidizing the losses with the profits from other segments. Similarly, entrenched and powerful CEOs may be unwilling to discontinue projects with losses either because they are reluctant to acknowledge their mistakes or because of some personal benefits from managing a larger firm. Third, a newly appointed CEO is more likely to perform an objective and critical review of the firm’s business operations, to shut down poorly performing divisions, and to consider new strategies that allow the firm to become profitable again than an incumbent CEO who might have strong preferences about his/her prior investments. In summary, a testable hypothesis is that CEO turnover is higher following accounting losses.
Our hypothesis has broader implications. Several valuation studies find that the relation between returns and earnings is weaker for loss firms than for profit firms (Collins et al. 1999, Burgstahler and Dichev 1997, Hayn 1995). The “liquidation/abandonment option” to redeploy existing assets is often used as an explanation for the differential results between firm values and earnings for profit and loss firms. Assuming that CEOs are willing to liquidate a firm or to discontinue a segment, when losses are expected to perpetuate, investors perceive losses as being temporary. Therefore, the stock market reaction to losses is muted.
However, in the presence of agency problems, it is less clear why CEOs might be willing to exercise the liquidation/abandonment option when losses are expected to continue. For example, Ofek (1993) finds that entrenched managers are reluctant to discontinue operations even when a firm is distressed. In general, prior studies do not directly address or specify what mechanisms ensure that even entrenched CEOs, or CEOs keen to build empires through value reducing acquisitions would liquidate or abandon a loss-making operation if losses are expected to continue.
Our study suggests that personal career concerns and higher frequency of CEO turnover following reporting of accounting losses ensure that the liquidation or abandonment 7

8. option is not delayed. If the incumbent CEO is dismissed by the board because the firm reported a loss, the successor CEO has no reasons to delay liquidating a division or reversing a strategy implemented by his/her predecessor. When a CEO is retained by the board despite reporting a loss, the incumbent CEO is as keen as a new CEO to exercise the liquidation/abandonment option because he/she is conscious that not doing so is likely to result in a dismissal by the board.
3. Research Design
We test the relationship between CEO turnover and accounting losses using the following logistic regression.
Turnover = β0+ β1Loss + β2Market-return + β3Asset-return + β4ΔEarnings + β5Stock-volatility + β6Earnings-volatility + β7Concentration + β8Size + β9Growth + β10Restructure + β11Restatement + β12Age + Industry/Year Fixed effects + ε (1)
Where Turnover is an indicator variable that equals 1 when there is a change in the CEO in the current or subsequent year and 0 otherwise. Our main independent variable is Loss, which is also an indicator variable with a value of 1 when net income is negative for the current year and 0 otherwise. The predicted sign of the coefficient on Loss is positive; CEO turnover for firms with losses is expected to be higher than firms with profits.
We include the following control variables which are measured one year prior to the year of the CEO turnover. Market-return is the difference between the raw returns and the value- weighted CRSP market returns over a twelve-month fiscal period. Asset-return is industry- adjusted return on assets measured as the difference between the firm-specific and the industry-median income before extraordinary items deflated by total assets at the beginning of the year. ΔEarnings is the difference between current period earnings before extraordinary items and the corresponding number in the prior year deflated by market value of equity at the beginning of the year. Stock-volatility is the standard deviation of Market-return based on prior twenty-four monthly returns. Earnings-volatility is the standard deviation of Asset-return over the
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9. previous five years. Concentration is the industry level Herfindahl index. Size is the logarithmic transformation of the fiscal year-end market value of equity. Growth is the sum of the market value of equity and the book value of debt scaled by the book value of total assets. Restructure is an indicator variable that equals 1 if special items as a percentage of total assets is less than or equal to -5 percent and 0 otherwise. Restatement is an indicator variable equal to 1 when a firm restates its financial statement in the current or prior year and 0 otherwise. Age is an indicator variable equal to 1 when the CEO is over the age of 60 years and 0 otherwise.
We include one market and two accounting measures of performance (Market-return, Asset-return, ΔEarnings) because prior studies find that CEO turnover is related poor performance (e.g., Farrell and Whidbee 2003, DeFond and Park 1999, Murphy and Zimmerman 1993, Weisbach 1988). We include two measures of volatility, one market (Stock-volatility) and another accounting (Earnings-volatility) because firms with higher volatility are more prone to severe shocks that lead to more frequent CEO turnovers (Engel et al. 2003, DeFond and Park 1999). We control for industry concentration because CEO turnover is greater in highly concentrated industries than in less concentrated industries (DeFond and Park 1999). We control for firm size (Size) and investment opportunity (Growth) because larger firms and growing firms have a greater demand for high quality CEOs (Smith and Watts 1992). We include indicator variables for restructuring activities (Restructure) and financial restatements (Restatement) because firms with structural or reporting problems are more likely to be associated with CEO turnovers (Desai et al. 2006, Pourciau 1993). Because not all CEO turnovers are performance related, as in DeFond and Park (1999), we include an indicator variable for CEOs who are 60 years or older (Age). Finally, we include fixed effects for years and industry to control for variations in CEO turnover over time and across industries.
We also estimate an augmented equation that includes several governance variables in addition to those control variables already included in Equation (1) because prior studies find 9

10. that CEO turnover is associated with board characteristics (e.g., Weisbach 1988, Goyal and Park 2002). Specially, we include the number of directors on the board (Board-size), the percentage of independent directors on the board (Board-independence), indicator variables when the CEO is also the board chair (CEO-duality) and when a firm has separate audit, nominating, and compensation committees (Separate-committees), and the percentage of common stock held by the five top executives (Ownership).
4. Data and Descriptive Statistics
4.1. Data and sample selection
Our sample consists of Standard and Poor’s (S&P) 1500 firms from Compustat’s ExecuComp files during the period 1997 to 2006. Included in the ExecuComp files are the names of the top five executives in the firm, a CEOANN variable indicating which of the five executives has the title of a CEO, and the starting date of the CEO. Our CEO turnover indicator variable is constructed from the information contained in ExecuComp files. If the name of the executive listed as a firm’s CEO for the current year is different from the one listed as the CEO for the prior year, we conclude that there was a change in the CEO, or a new CEO was hired, for the current year. Because we define Turnover as one when there is a change in a CEO for the current or subsequent year, and our sample period ends with 2006, we consider accounting loss from 1997 to 2005. We also obtain the five top executive stock ownership and CEO age data from the ExecuComp files.
The data on earnings and other firm characteristics are obtained from Compustat annual files. Stock return data are obtained from CRSP files. We obtain board characteristics (size, composition, and structure) from the RiskMetrics database (also previously known as IRRC). We construct one combined sample by merging the CEO, accounting, stock return, and governance data. To remove the effect of outliers, we winsorize the top or bottom 1 percent of the observations for Market-return, Asset-return, ΔEarnings, Earnings-volatility, Concentration,
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11. and Growth.3 This sample selection procedure results in 11,738 firm-year observations over fiscal years 1997 through 2005 with information about CEO turnover included up to 2006.
4.2. Descriptive statistics
Panel A of Table 1 reports the descriptive statistics for the variables included in Equation (1). CEO turnover levels are higher than those typically reported by prior studies; the frequency of CEO turnover is 23.6% over the entire sample period. The difference in turnover levels between our study and prior studies is attributable to the measurement of our CEO turnover variable. CEO turnover is generally measured for any given year while we measure turnover for the current and subsequent year. Losses are fairly common; of all the firm years, 17.5% report negative net income. The mean (median) cumulative market-adjusted stock returns (Market- return) are 0.085 (0.017). The mean (median) industry-adjusted return on assets (Asset-return) and changes in earnings before extraordinary items deflated by market value of equity (ΔEarnings) are 0.050 (0.029) and 0.011 (0.006), respectively. The mean (median) return volatility (Stock-volatility) is 0.116 (0.104), whereas the mean (median) earnings volatility (Earnings-volatility) is 0.057 (0.030). The Herfindahl index (Concentration) has a median of 0.041. The mean fiscal-year end market value of equity (Market-equity) is $7.2 billion, while the median number is much smaller ($1.36 billion). The mean (median) market-to-book ratio (Growth) is 1.70 (1.20). 8.5% of firm years report special items less than or equal to -5 percent of total assets and 8.9% of firm years are involved with restatements in the current or prior year. The mean and median values of CEO age are very close; the median CEO age is 56.
Panel B of Table 1 reports the summary statistics for the CEO turnover and non-turnover samples and the significance of the difference in means between the two samples. We find that losses are more frequent for CEO turnover firms. 25.5% of the CEO turnover sample has losses, while the corresponding number for the non-turnover sample is 15.1%. The difference in Loss
3Our results are not sensitive to other outlier identification methods and they remain qualitatively unchanged when we remove the top and/or bottom 0.5 or 1 percent of observations or even retain all the outliers.
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12. (10.4%) is statistically significant at the 1 percent level. As in prior studies, we also find that, compared to non-turnover firms, CEO turnover firms have lower stock market and accounting performance, are riskier, have lower growth opportunities, restate their financial statements more frequently, and have older CEOs. The mean difference of two other variables, Concentration and Market-equity, is not significant.
Table 2 presents the relative frequency of CEO turnover for firms reporting losses and firms reporting profits. Consistent with our expectations that accounting losses are more likely to lead to a CEO turnover, Turnover in Panel A is higher among loss firms than among profit firms. More specifically, the frequency of a CEO turnover for the current or subsequent year is 34% when firms report negative net income while the corresponding number is 21% when firms report a non-negative number as net income. The difference in frequency in turnover between the two groups of firms is statistically significant at the 1 percent level. Thus, our preliminary results indicate that firms with losses have a higher chance of being associated with current or future CEO turnover than firms with profits.
Panel B of Table 2 reports the frequency of CEO turnover for loss and profit firms from 1997 to 2005. The frequency of CEO turnover for firms reporting profits appears to be constant around 20% over the sample years. On the other hand, the frequency of CEO turnover for firms reporting losses fluctuates over time. However, the difference in the frequency of CEO turnover between loss and profit firms is statistically significant for each of the sample years indicating that our hypothesis that losses lead to higher CEO turnover is statistically reliable across each of the years.
5. Empirical Results
5.1. CEO turnover and accounting losses
Table 3 presents the logistic regression results for Equation (1) that predicts the probability of top executive turnover following losses. The dependent variable Turnover is an indicator variable that equals 1 when there is a change in the CEO in the current or subsequent 12

13. year and 0 otherwise. Our interest is in the sign and magnitude of the coefficient on Loss. Consistent with our expectations and with our univariate results, we find a statistically and economically significant relationship between CEO turnover and accounting losses. The coefficient on Loss is 0.655 (χ2=155.48) in the first regression without the control variables. The coefficient on Loss remains positive and significant (0.586; χ2=86.09) in the second regression when we include other variables such as the market and accounting measures of firm performance. The economic magnitude of the coefficient is large. Holding the control variables at their mean values, the probability of a CEO losing his/her job within two years of reporting a loss is 32 percent, while the corresponding number for profit firms is 21 percent. Thus, the likelihood of CEO turnover for loss firms is about 52 percent larger than that for profit firms.
The results of the control variables are generally consistent with our expectations and similar to those reported in prior studies. The coefficient estimate on Market-return is negative and significant, which indicates that poor stock performance significantly increases the likelihood of CEO turnover. In contrast, the coefficient estimates on Stock-volatility, Size, Restructure, Restatement, and Age are all positive and significant. The results suggest that the likelihood of CEO turnover is higher for firms with higher volatility, larger firms with restructuring activities and financial restatements, and firms with older CEOs. The coefficients on Asset- return, ΔEarnings, Earnings-volatility, Concentration, and Growth are insignificant.
Our analysis in Table 3 relies on net income to partition firms into profit and loss groups because net income is the bottom-line measure of accounting performance which includes core, non-core, and discontinued operations, cumulative effect of accounting changes, and losses attributable to minority interest. We additionally consider two other earnings measures: (1) income before extraordinary items and (2) operating income. The first measure captures earnings from core and non-core operations, while the second measure includes only earnings from core operations. 13

14. Table 4 reports the regression results, using these alternative measures of reported earnings to define Loss. Our results suggest that all the measures of reported earnings are associated with a higher likelihood of a CEO turnover. Controlling for the other determinants of CEO turnover−such as market and accounting measures of performance, volatility of market and accounting performance, industry concentration, firm size, growth opportunities, restructuring activities, financial restatements, and CEO age−the coefficient on Loss in Panel A is 0.586 (χ2=86.09), 0.562 (χ2=74.16), and 0.305 (χ2=8.11), respectively, when Loss is defined using net income, income before extraordinary items, and operating income as alternative measures of reported earnings. As indicated in Panel B, the magnitude of the coefficient on Loss is the largest when Loss is based on net income, but it is the smallest when Loss is based on operating income. Our results suggest that boards tend to focus on the bottom line number for holding CEOs accountable for losses.
One concern with Table 3 is that our regression specification excludes governance measures for various agency problems which might impact CEO turnover and also be associated with the likelihood of a firm reporting a loss. For instance, a CEO with a higher equity ownership in the firm has more power because greater equity ownership might affect CEO turnover decisions. Similarly, a more independent, effective and diligent board is more likely to hold a CEO accountable for poor performance than one that is less effective. Accordingly, we additionally include the size, composition, and structure of the board and managerial ownership in Equation (1). Specifically, we include the number of members on the board (Board-size), the percentage of independent directors on the board (Board-independence), the combination of CEO and board chair positions (CEO-duality), the presence of separate standing sub- committees (Separate-committees), and the percentage of common stock held by the top five executives (Ownership). The additional data requirement reduces our sample to 7,516 firm-year observations.
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15. The results in Table 5 show that the inclusion of the additional board and ownership variables does not alter the relation between CEO turnover and accounting losses. Consistent with the results in Tables 3 and 4, the positive relation between CEO turnover and losses continues to hold. The coefficient on Loss is 0.621 (χ2=77.92) and 0.552 (χ2=43.71), respectively, without and with the control variables in the first and second regressions. The parameter estimate in the second regression suggests that, based on the mean values of the control variables, the probability of a CEO losing a job within two years of reporting a loss is 29 percent, while that of a CEO reporting a profit is 19 percent. We also find that, consistent with the findings in prior studies (e.g., Goyal and Park 2002, Ghosh et al. 2010), the coefficient on CEO-duality is negative and significant, suggesting that firms with combined CEO-Chair positions have lower turnover than firms with separate positions. The coefficients on Board-size, Board-independence, Separate-committees, and Ownership are all insignificant.
Overall, the results from Tables 3 to 5 suggest that CEOs reporting losses are more likely to lose their jobs within the two-year period following losses including the year of the loss, compared to CEOs reporting profits, which is consistent with our hypothesis.
5.2. CEO turnover and sustained accounting losses
Prior studies show that debt and equity markets reward firms with sustained earnings growth because sustained earnings increases are indicative of the firms’ competitive advantages and a higher probability of future earnings and cash flow growth (Elliott et al. 2010, Ghosh et al. 2005, Barth et al. 1999). Similar to the studies on the information contents of sustained earnings growth, we analyze whether sustained accounting losses affect the likelihood of a CEO turnover. To measure sustained losses, we decompose Loss into 5 indicator variables depending on the number of years of consecutive annual losses. Loss1 equals 1 for firms with a loss in the current year but not in the prior year (i.e., NIt<0 and NIt-1≥0). Loss2 equals 1 for firms with two consecutive years of losses (i.e., NIt<0, NIt-1<0, and NIt-2≥0). Similarly, Loss3, 15

16. Loss4, and Loss5 equal 1 for firms with 3, 4, and 5 or more years of consecutive losses, respectively.
Table 6 presents the regression results of CEO turnover on sustained losses. We find evidence on the dampening effect of a sustained loss on the likelihood of CEO turnover. While the coefficients on Loss1, Loss2, and Loss3 are all positive and significant in the first regression with the control variables, the magnitude of the coefficients decreases as the length of sustained loss period increases. The coefficients on Loss4 and Loss5 are insignificant.
In the second regression when we add the governance variables, the coefficients on Loss1 and Loss2 remain positive and significant; they are 0.600 (χ2=35.33) and 0.565 (χ2=15.25), respectively. Our results indicate that the effect of losses on CEO turnover is the strongest for firms with a loss in the current year. Further, controlling for the current period loss, CEOs are more likely to be dismissed when firms report losses over two consecutive years. However, the coefficients on Loss3, Loss4, and Loss5 are insignificant, indicating that losses sustained over three or more years do not increase the chances of a CEO turnover. These results may suggest that boards of directors play a proactive role in replacing a poorly performing CEO before matters even get worse which is one explanation why investors treat losses as being temporary.
5.3. Outside replacement and accounting losses
The decision to fire a poorly performing CEO benefits shareholders only when the board appoints a more capable successor. CEOs who are appointed from outside the firm are more likely to change pre-existing firm policies that resulted in losses. Borokhovich et al. (1996) find that the stock market views the appointment of an outsider to the CEO position more favorably than the appointment of an insider, especially when the incumbent CEO is forced to resign. Therefore, we also examine whether accounting losses increase the likelihood of an outside replacement to send a strong signal to investors that the CEO is committed turning around the firm from a loss making firm to one making profits. We hand collect data to establish whether
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17. the successor CEO is from outside the firm by reading press releases, 10-K reports, and associated proxy statements. The sample to examine the impact of losses on outside appointments consists of 1,483 CEO turnover observations.
Table 7 presents the regression results on the relationship between accounting losses and the likelihood of outside succession, conditional on CEO turnover. We estimate Equation (1) using a dichotomous dependent variable that equals 1 when the incumbent CEO is replaced with a successor CEO from outside the firm and 0 if the replacement CEO is appointed from within the firm. We find that the coefficient on Loss is positive and significant; it is 0.450 (χ2=7.96) and 0.488 (χ2=6.38), respectively, when we exclude and include the governance variables in the first and second regressions. The parameter estimate in the second regression suggests that, based on the mean values of the governance and control variables, the probability of an outside appointment for firms reporting a loss is 29 percent, while that for firms reporting a profit is 20 percent. Our results suggest that accounting losses lead to more frequent appointments of CEOs from outside the firm.
We also find that the coefficient on Separate-committees is positive and significant, which indicates that the likelihood of outside succession is higher for firms with specialized committees on audit, appointment, and remuneration issues. Among the control variables, we find that the coefficients on Market-return, Size, and Age are negative and significant, implying that the boards of larger firms with higher stock performance and older CEOs tend to hire an insider to replace the incumbent CEO.
6. Sensitivity Analysis
6.1. Endogeneity
A potential concern with our prior results is that accounting losses are likely to be endogenously determined (Klein and Marquardt 2006, Joos and Plesko 2005), which suggests that the coefficient estimates from the regressions might be biased and inconsistent. We 17

18. address any endogeneity concerns using a two stage least squares (2SLS) estimation procedure to obtain consistent and efficient estimates for losses. Specifically, drawing on prior studies, we model losses in the first stage and then in the second stage we regress CEO turnover on the probability of a firm reporting a loss obtained from the first stage regression.
The results for the first stage estimation are presented in the first column of Table 8. The coefficients on Cash-flow, Accrual, Dividend, and Size are all negative and significant, which suggests that firms with higher cash flow from operations, larger accruals, and larger firms paying dividend are less likely to report accounting losses. In contrast, the coefficient on lag(Loss) is positive and significant, indicating that firms with losses in the prior year are more likely to incur losses in the current year.
In the second stage, we use the estimated values of losses from the first stage as an instrumental variable and re-estimate Equation (1). After controlling for the endogeneity of accounting losses, our results confirm the earlier findings on the positive relationship between CEO turnover and losses. The coefficient on Pred-Loss is 0.648 (χ2=8.81) and 0.501 (χ2=4.15) when we exclude and include the governance variables in the second and third columns, respectively. Thus, our results once again confirm that the likelihood of CEO turnover is higher for firms reporting accounting losses.
6.2. Magnitude of losses
Our analysis adopts the indicator variable Loss to examine the relation between accounting losses and CEO turnover. Using the indicator variable to represent negative net income, we presume that the impact of losses on CEO turnover does not depend on the magnitude of accounting losses. Thus, as part of our sensitivity analyses, we examine whether the strength of the relation between losses and turnover varies with the size of losses by adding Magnitude which is the absolute value of net income deflated by book value of equity at the beginning of the year.
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19. Table 9 reports the results after including the interaction term between Magnitude and Loss to estimate how Magnitude affects the sensitivity of top executive turnover to losses. Our results on accounting losses continue to hold; the coefficient on Loss remains positive and significant in the first and second regressions without and with Magnitude. Similarly, the coefficient on Loss×Magnitude is positive and significant; it is 0.609 (χ2=12.30) and 0.700 (χ2=8.66) in the first and second regressions, indicating that the sensitivity of CEO turnover to accounting losses becomes larger as the magnitude of accounting losses increases. Our results suggest that boards take into account both incidence and size of accounting losses in removing poorly-performing CEOs.
6.3. The effect of governance on the relationship between CEO turnover and losses
Goyal and Park (2002) examine how the leadership structure of the board affects the sensitivity of CEO turnover to firm performance and find that the sensitivity of CEO turnover to market-adjusted stock return is less for firms with CEO duality than for firms with separate positions. Accordingly, we also examine whether governance characteristics affect the sensitivity of turnover to losses by augmenting the logistic regressions reported in Table 5 after additionally including interactions between accounting losses and the five governance variables described earlier.
In unreported results, we find that the inclusion of interactions has no effect on our results presented in Table 5. The coefficient on CEO-duality remains negative and significant, while the coefficients on the other four governance variables also continue to remain insignificant. Further, we find that the coefficients on Loss×CEO-duality and Loss×Separate- committees are both positive and significant. These results suggest that the sensitivity of top executive turnover to accounting losses is higher for firms with separate subcommittees and firms with combined CEO and chairman positions. In the contrast to the results on CEO-duality whose coefficient is negative, the coefficient on Loss×CEO-duality is positive. Because the
19

20. interaction term capture the marginal effect of CEO-duality on CEO turnover for loss firms relative to profit firms, our results suggest that CEO-duality becomes less influential in affecting CEO turnover for loss firms.
7. Conclusions
Several studies examine the importance of earnings and stock returns as measures of firm performance on CEO turnover considerations (e.g., Weisbach 1988, Murphy and Zimmerman 1993, Goyal and Park 2002). We suggest that accounting losses reflect managerial effort and quality that are not fully captured in the traditional measures of firm performance. In this paper, we investigate whether accounting losses provide information that can be used to assess CEO retention/dismissal decision. Specifically, we examine whether accounting losses lead to subsequent top executive turnover.
Based on a comprehensive sample of CEO turnover between 1997 and 2005, we find that compared to profit firms, the likelihood of CEO turnover is significantly higher for loss firms. Controlling for the other determinants of CEO turnover that include traditional market and accounting measures of firm performance, the relative probability of a CEO losing a job within two years is about 52 percent higher for firms reporting losses than firms reporting profits. Also, when we use two other reported earnings measures (income before extraordinary items and operating income) in addition to the bottom-line number (net income) to define accounting losses, we find a positive relation between turnover and losses for all the three measures used to define losses. However, the sensitivity of CEO turnover to losses is the strongest when losses are defined using the bottom line net income number. Further, when we include the size, composition, and structure of the board and managerial ownership in our regression specifications, we find that inclusion of these additional governance variables does not alter the effect of accounting losses on CEO turnover. Our results on the relation between turnover and losses are also robust to the endogeneity of accounting losses and inclusion of magnitude of accounting losses. 20

21. Moreover, we examine whether sustained accounting losses affect the likelihood of CEO turnover and find that CEOs are more likely to be dismissed when firms report losses in the current year or over two consecutive years but not when earnings are sustained over longer periods which suggests that boards are more proactive in disciplining poorly performing managers. We also examine whether accounting losses increase the likelihood of outside replacement. We find that accounting losses lead to more frequent appointments of CEOs from outside the firm. The probability of an outside appointment is 29 percent and 20 percent, respectively, for loss firms and profit firms.
Our results suggest that while boards incorporate accounting and market measures of performance in evaluating management, they view losses as an indicator of management failure and consequently penalize CEOs for reporting losses. Additionally, prior studies often presume that managers exercise the liquidation/abandonment option when losses are expected to persist and, therefore, investors view negative earnings as having low information content relative to positive earnings. However, the literature is silent why management will not continue to subside their pet projects or invest in negative net present value projects when such projects benefit their personal welfare. Our results suggest that CEO turnover or the threat of a higher turnover following losses ensures that CEOs will exercise the liquidation/abandonment option. Finally, our results also provide one explanation why firms manage earnings to avoid reporting losses. 21

22. References
Barth, M. E., J. A. Elliott, and M. A. Finn, 1999, Market rewards associated with patterns of increasing earnings, Journal of Accounting Research 37, 387-413.
Borokhovich, K. A., R. Parrino, and T. Trapani, 1996, Outside directors and CEO selection, Journal of Financial and Quantitative Analysis 31, 337-355.
Burgstahler, D., and I. Dichev, 1997, Earnings management to avoid earnings decreases and losses, Journal of Accounting and Economics 24, 99-126.
Collins, D. W., M. Pincus, and H. Xie, 1999, Equity valuation and negative earnings: The role of book value of equity, The Accounting Review 74, 29-62.
DeAngelo, H., L. DeAngelo, and D. J. Skinner, 1992, Dividends and losses, Journal of Finance 58, 1837-1863.
Dechow, P., S. Richardson, and I. Tuna, 2003, Why are earnings kinky? An examination of the earnings management explanation, Review of Accounting Studies 8, 355-384.
Dechow, P., and R. Sloan, 1991, Executive incentives and the horizon problem, Journal of Accounting and Economics 14, 51-89.
DeFond, M. L., and C. W. Park, 1999, The effect of competition on CEO turnover, Journal of Accounting and Economics 27, 35-56.
Desai, H., C. E. Hogan, and M. S. Wilkins, 2006, The reputational penalty for aggressive accounting: Earnings restatements and management turnover, The Accounting Review 81, 83-112.
Durtschi, C., and P. Easton, 2005, Earnings management? The shapes of the frequency distributions of earnings metrics are not evidence ipso facto, Journal of Accounting Research 43, 557-592.
Elliott, J. A., A. Ghosh, and D. Moon, 2010, Asymmetric valuation of sustained growth by bond- and equity-holders, Review of Accounting Studies, Forthcoming.
Engel, E., R. M. Hayes, and X. Wang, 2003, CEO turnover and properties of accounting information, Journal of Accounting and Economics 36, 197-226.
Farrell, K. A., and D. A. Whidbee, 2003, Impact of firm performance expectations on CEO turnover and replacement decisions, Journal of Accounting and Economics 36, 165-196.
Ghosh, A., Z. Gu, and P. Jain, 2005, Sustained earnings and revenue growth, earnings quality, and earnings response coefficients, Review of Accounting Studies 10, 33-57.
Ghosh, A., C. Karuna, and D. Moon, 2010, When the CEO is also the chair of the board, Working paper, Baruch College, New York, NY. 22

23. Goyal, V., and C. Park, 2002, Board leadership structure and CEO turnover, Journal of Corporate Finance 8, 49-66.
Graham, J. R., C. R. Harvey, and S. Rajgopal, 2005, The economic implications of corporate reporting, Journal of Accounting and Economics 40, 3-73.
Hayn, C., 1995, The information content of losses, Journal of Accounting and Economics 20, 125-154.
Huson, M. R., R. Parrino, and L. T. Starks, 2001, Internal monitoring mechanisms and CEO turnover: A long-term perspective, Journal of Finance 55, 2265-2297.
Joos, P., and G. Plesko, 2005, Valuing loss firms, The Accounting Review 80, 847-870.
Kaplan, S., and B. A. Minton, 2006, How has CEO turnover changed? Increasingly performance sensitive boards and increasingly uneasy CEOs, Working paper, University of Chicago, Chicago, IL.
Klein, A., and C. Marquardt, 2006, Fundamentals of accounting losses, The Accounting Review 81, 179-8206.
Murphy, K. J., 1999. Executive compensation, In O. Ashenfelter and D. Card (eds.), Handbook of Labor Economics. Volume 3, North Holland, 2485-2525.
Murphy, K. J., and J. Zabonjik, 2004, Managerial capital and the market for CEOs, Working paper, University of Southern California, Los Angeles, CA.
Murphy, K. J., and J. L. Zimmerman, 1993, Financial performance surrounding CEO turnover, Journal of Accounting and Economics 16, 273-315.
Ofek, E., 1993, Capital structure and firm response to poor performance, Journal of Financial Economics 34, 3-30.
Pinnuck, M., and A. Lillis, 2007, Profits versus losses: Does reporting an accounting loss act as a heuristic trigger to exercise the abandonment option and divest employees?, The Accounting Review 82, 1031-1053.
Pourciau, S., 1993, Earnings management and nonroutine executive change, Journal of Accounting and Economics 16, 317-336.
Roychowdhury, S., 2006, Earnings management through real activities manipulation, Journal of Accounting and Economics 42, 335-370.
Smith, C. W., and R. L. Watts, 1992, The investment opportunity set and corporate financing, dividend, and financing policies, Journal of Financial Economics 32, 262-292.
Watts, R. L., 2003, Conservatism in accounting, Part I: Explanations and implications, Accounting Horizons 17, 207-221.
23

24. Weisbach, M., 1988, Outside directors and CEO turnover, Journal of Financial Economics 20, 431- 460.
24

25. Table 1
Descriptive Statistics
Mean
1st Quartile
Median
3rd Quartile
Std. Dev.
Panel A: Full Sample
Turnover
0.236
0.000
0.000
0.000
0.424
Loss
0.175
0.000
0.000
0.000
0.380
Market-return
0.085
-0.235
0.017
0.293
0.520
Asset-return
0.050
-0.002
0.029
0.096
0.115
ΔEarnings
0.011
-0.010
0.006
0.029
0.089
Stock-volatility
0.116
0.074
0.104
0.147
0.055
Earnings-volatility
0.057
0.013
0.030
0.065
0.080
Concentration
0.057
0.027
0.041
0.067
0.048
Market-equity
7.159
0.517
1.360
4.537
23.913
Growth
1.697
0.833
1.202
1.966
1.502
Restructure
0.085
0.000
0.000
0.000
0.279
Restatement
0.089
0.000
0.000
0.000
0.286
Age
56.204
51.000
56.000
61.000
7.491
CEO Turnover
Yes
No
Differences
Panel B: Firms with and without CEO Turnover
Loss
0.255
0.151
0.104**
Market-return
0.006
0.110
-0.104**
Asset-return
0.037
0.054
-0.017**
ΔEarnings
0.003
0.013
-0.010**
Stock-volatility
0.120
0.115
0.005**
Earnings-volatility
0.062
0.056
0.006**
Concentration
0.056
0.057
-0.001
Market-equity
7.870
6.939
0.931
Growth
1.638
1.716
-0.078*
Restructure
0.115
0.076
0.039**
Restatement
0.111
0.083
0.028**
Age
58.085
55.622
2.463**
Turnover is an indicator variable that equals 1 when there is a change in the CEO in the current or subsequent year and 0 otherwise. Loss is an indicator variable with a value of 1 when net income is negative for the current year and 0 otherwise. Market-return is the difference between the raw returns and the value-weighted CRSP market returns over a twelve-month fiscal period. Asset-return is the industry-adjusted return on assets measured as the difference between the firm-specific and the industry-median income before extraordinary items deflated by total assets at the beginning of the year. ΔEarnings is the difference between current period earnings before extraordinary items and the corresponding number in the prior year deflated by market value of equity at the beginning of the year. Stock-volatility is the standard deviation of Market-return based on prior twenty-four monthly returns. Earnings-volatility is the standard deviation of Asset-return over the previous five years. Concentration is the industry level Herfindahl index. Market-equity is the fiscal year-end market value of equity. Growth is the sum of the market value of equity and the book value of debt scaled by the book value of total assets. Restructure is an indicator variable that equals 1 if special items as a percentage of total assets is less than or equal to -5 percent and 0 otherwise. Restatement is an indicator variable equal to 1 when a firm restates its financial statement in the current or prior year and 0 otherwise. Age is the age of the CEO in years (for the outgoing CEO in turnover firms) as of the fiscal-year end. Panel A is based on the full sample with 11,738 firm-year observations between 1997 and 2005, while Panel B is based on the samples with and without CEO turnover (2,772 and 8,966 observations, respectively). The significance test of differences in means between firms with and without CEO turnover is based on the t-tests.
** and * denote significance at the 1 percent and 5 percent level, respectively, for a two-tailed test.
25

26. Table 2
CEO Turnover for Firms with Losses and Profits
Firms with
Profits
Losses
Differences
Panel A: Full sample
0.213
0.343
-0.130**
Panel B: By fiscal year
1997
0.207
0.414
-0.207**
1998
0.217
0.349
-0.132**
1999
0.230
0.425
-0.195**
2000
0.257
0.458
-0.201**
2001
0.214
0.302
-0.088**
2002
0.186
0.285
-0.099**
2003
0.189
0.283
-0.094**
2004
0.210
0.302
-0.092**
2005
0.206
0.414
-0.208**
The percentage of CEO turnover for firms reporting profits and losses. Firms with losses have negative net income for the current year and rest of the firms are classified as profit firms. The significance test of differences in means between profit and loss firms is based on the t-tests.
** denotes significance at the 1 percent level for a two-tailed test. 26

27. Table 3
CEO Turnover and Losses
Dependent variable: Turnover
(1)
(2)
Intercept
-1.304 (2764.95)**
-2.286 (172.98)**
Loss
0.655 (155.48)**
0.586 (86.09)**
Control variables
Market-return
-0.292 (31.99)**
Asset-return
-0.463 (2.95)
ΔEarnings
-0.209 (0.52)
Stock-volatility
1.735 (7.34)**
Earnings-volatility
0.020 (0.01)
Concentration
-0.284 (0.25)
Size
0.078 (23.25)**
Growth
-0.007 (0.13)
Restructure
0.183 (4.49)*
Restatement
0.334 (19.02)**
Age
0.639 (172.05)**
Fixed effects
Industry and Year
Observations
11,738
11,738
Nagelkerke R2
1.89%
6.11%
The probability estimates of a CEO Turnover when firms report a loss. The dependent variable Turnover is an indicator variable that equals 1 when there is a change in the CEO in the current or subsequent year and 0 otherwise. The independent variables are as follows. Loss is an indicator variable with a value of 1 when net income is negative for the current year and 0 otherwise. Market-return is the difference between the raw returns and the value-weighted CRSP market returns over a twelve-month fiscal period. Asset-return is the industry-adjusted return on assets measured as the difference between the firm-specific and the industry-median income before extraordinary items deflated by total assets at the beginning of the year. ΔEarnings is the difference between current period earnings before extraordinary items and the corresponding number in the prior year deflated by market value of equity at the beginning of the year. Stock-volatility is the standard deviation of Market-return based on prior twenty-four monthly returns. Earnings-volatility is the standard deviation of Asset-return over the previous five years. Concentration is the industry level Herfindahl index. Size is the logarithmic transformation of the fiscal year-end market value of equity. Growth is the sum of the market value of equity and the book value of debt scaled by the book value of total assets. Restructure is an indicator variable that equals 1 if special items as a percentage of total assets is less than or equal to -5 percent and 0 otherwise. Restatement is an indicator variable equal to 1 when a firm restates its financial statement in the current or prior year and 0 otherwise. Age is an indicator variable equal to 1 when the CEO is over the age of 60 years and 0 otherwise. All the variables except Restatement are measured one year prior to the year of the CEO turnover. We report the estimated coefficients from a logistic regression and the corresponding χ2–statistics in parenthesis.
** and * denote significance at the 1 percent and 5 percent level, respectively, for a two-tailed test.
27

28. Table 4
CEO Turnover and Losses: Alternative Earnings Measures
Dependent Variable: Turnover
Negative:
Net Income
Income before extraordinary items
Operating income
Panel A: Firms with negative earnings
Loss
0.586 (86.09)**
0.562 (74.16)**
0.305 (8.11)**
Control variables
Included
Included
Included
Observations
11,738
11,738
11,738
Nagelkerke R2
6.11%
5.96%
5.15%
Panel B: Differences in the estimated coefficients
Loss is negative net income
0.586
Loss is negative income before extraordinary items
Difference in estimated coefficients
0.024
Loss is negative net income
0.586
Loss is negative operating income
Difference in estimated coefficients
0.281
Loss is negative income before extraordinary items
0.562
Loss is negative operating income
Difference in estimated coefficients
0.257
The probability estimates of a CEO Turnover when firms report a loss. The dependent variable Turnover is an indicator variable that equals 1 when there is a change in the CEO in the current or subsequent year and 0 otherwise. Loss is an indicator variable with a value of 1 when earnings is negative for the current year and 0 otherwise. Earnings is defined as net income, income before extraordinary items, and operating income. The control variables are the same as those included in Table 3. We report the estimated coefficients from a logistic regression and the corresponding χ2–statistics in parenthesis.
** denotes significance at the 1 percent level for a two-tailed test. 28

29. Table 5
CEO Turnover and Losses: Including Governance Characteristics
Dependent Variable: Turnover
(1)
(2)
Intercept
-1.291 (63.52)**
-2.261 (71.11)**
Loss
0.621 (77.92)**
0.552 (43.71)**
Governance variables
Board-size
0.040 (15.16)**
0.015 (1.36)
Board-independence
-0.001 (1.06)
-0.000 (0.02)
CEO-duality
-0.456 (60.70)**
-0.633 (102.36)**
Separate-committees
0.024 (0.10)
0.121 (2.11)
Ownership
-0.003 (0.64)
-0.005 (1.41)
Control variables
Market-return
-0.273 (14.68)**
Asset-return
-0.367 (0.91)
ΔEarnings
-0.172 (0.16)
Stock-volatility
1.496 (3.07)
Earnings-volatility
-0.373 (0.46)
Concentration
-0.399 (0.30)
Size
0.079 (10.47)**
Growth
0.012 (0.18)
Restructure
0.258 (4.97)*
Restatement
0.357 (15.89)**
Age
0.874 (194.20)**
Fixed effects
Industry and Year
Observations
7,516
7,516
Nagelkerke R2
2.98%
8.71%
The probability estimates of a CEO Turnover when firms report a loss. The dependent variable Turnover is an indicator variable that equals 1 when there is a change in the CEO in the current or subsequent year and 0 otherwise. The independent variables are as follows. Loss is an indicator variable with a value of 1 when net income is negative for the current year and 0 otherwise. Board-size is the number of directors on the board. Board-independence is the percentage of independent directors on the board. CEO-duality and Separate-committees are indicator variables set to 1 when the CEO is also the board chair and when a firm has separate audit, nominating, and compensation committees, respectively. Ownership is the percentage of common stock held by the five top executives. Market- return is the difference between the raw returns and the value-weighted CRSP market returns over a twelve-month fiscal period. Asset-return is the industry-adjusted return on assets measured as the difference between the firm- specific and the industry-median income before extraordinary items deflated by total assets at the beginning of the year. ΔEarnings is the difference between current period earnings before extraordinary items and the corresponding number in the prior year deflated by market value of equity at the beginning of the year. Stock-volatility is the standard deviation of Market-return based on prior twenty-four monthly returns. Earnings-volatility is the standard deviation of Asset-return over the previous five years. Concentration is the industry level Herfindahl index. Size is the logarithmic transformation of the fiscal year-end market value of equity. Growth is the sum of the market value of equity and the book value of debt scaled by the book value of total assets. Restructure is an indicator variable that equals 1 if special items as a percentage of total assets is less than or equal to -5 percent and 0 otherwise. Restatement is an indicator variable equal to 1 when a firm restates its financial statement in the current or prior year and 0 otherwise. Age is an indicator variable equal to 1 when the CEO is over the age of 60 years and 0 otherwise. All the variables except Restatement are measured one year prior to the year of the CEO turnover. We report the estimated coefficients from a logistic regression and the corresponding χ2–statistics in parenthesis.
** and * denote significance at the 1 percent and 5 percent level, respectively, for a two-tailed test.
29

30. Table 6
CEO Turnover and Sustained Losses
Dependent Variable: Turnover
(1)
(2)
Intercept
-2.189 (180.12)**
-2.239 (69.64)**
Loss1
0.614 (64.78)**
0.600 (35.33)**
Loss2
0.608 (28.75)**
0.565 (15.25)**
Loss3
0.437 (8.56)**
0.382 (3.71)
Loss4
0.118 (0.32)
0.030 (0.01)
Loss5
0.281 (1.39)
0.367 (2.12)
Governance variables
Not Included
Included
Control variables
Included
Included
Observations
11,738
7,516
Nagelkerke R2
6.09%
8.77%
The probability estimates of a CEO Turnover when firms report a loss. The dependent variable Turnover is an indicator variable that equals 1 when there is a change in the CEO in the current or subsequent year and 0 otherwise. Loss is decomposed into 5 indicator variables depending on the number of years of consecutive annual losses. Loss1 equals 1 for firms with a loss in the current year but not in the prior year. Similarly, Loss2, Loss3, Loss4, and Loss5 equal 1 for firms with 2, 3, 4, and 5 or more years of consecutive losses, respectively. The governance and control variables are the same as those included in Table 5. We report the estimated coefficients from a logistic regression and the corresponding χ2–statistics in parenthesis.
** denotes significance at the 1 percent level for a two-tailed test. 30

31. Table 7
Probability of an Outside CEO Appointment Conditional on CEO Turnover
Dependent Variable: Outsider Replacement
(1)
(2)
Intercept
-0.006 (0.01)
0.248 (0.11)
Loss
0.450 (7.96)**
0.488 (6.38)*
Governance variables
Board-size
-0.032 (0.69)
Board-independence
0.000 (0.01)
CEO-duality
0.262 (2.74)
Separate-committees
0.587 (5.71)*
Ownership
-0.023 (3.02)
Control variables
Market-return
-0.254 (3.11)
-0.489 (5.55)*
Asset-return
-0.008 (0.01)
-0.123 (0.02)
ΔEarnings
-0.441 (0.42)
0.395 (0.15)
Stock-volatility
-0.261 (0.02)
1.282 (0.33)
Earnings-volatility
1.124 (1.34)
-0.240 (0.02)
Concentration
-1.296 (0.57)
0.048 (0.01)
Size
-0.123 (7.31)**
-0.153 (5.34)*
Growth
0.039 (0.47)
0.012 (0.02)
Restructure
0.180 (0.76)
0.246 (0.89)
Restatement
-0.046 (0.07)
-0.161 (0.60)
Age
-0.537 (14.25)**
-0.625 (13.60)**
Fixed effects
Industry and Year
Industry and Year
Observations
1,483
1,128
Nagelkerke R2
10.34%
14.01%
The dichotomous dependent variable Outsider Replacement equals 1 when the incumbent CEO is replaced with a successor CEO from outside the firm and 0 if the replacement CEO is appointed from within the firm. The independent variables are as follows. Loss is an indicator variable with a value of 1 when net income is negative for the current year and 0 otherwise. Board-size is the number of directors on the board. Board-independence is the percentage of independent directors on the board. CEO-duality and Separate-committees are indicator variables set to 1 when the CEO is also the board chair and when a firm has separate audit, nominating, and compensation committees, respectively. Ownership is the percentage of common stock held by the five top executives. Market- return is the difference between the raw returns and the value-weighted CRSP market returns over a twelve-month fiscal period. Asset-return is the industry-adjusted return on assets measured as the difference between the firm- specific and the industry-median income before extraordinary items deflated by total assets at the beginning of the year. ΔEarnings is the difference between current period earnings before extraordinary items and the corresponding number in the prior year deflated by market value of equity at the beginning of the year. Stock-volatility is the standard deviation of Market-return based on prior twenty-four monthly returns. Earnings-volatility is the standard deviation of Asset-return over the previous five years. Concentration is the industry level Herfindahl index. Size is the logarithmic transformation of the fiscal year-end market value of equity. Growth is the sum of the market value of equity and the book value of debt scaled by the book value of total assets. Restructure is an indicator variable that equals 1 if special items as a percentage of total assets is less than or equal to -5 percent and 0 otherwise. Restatement is an indicator variable equal to 1 when a firm restates its financial statement in the current or prior year and 0 otherwise. Age is an indicator variable equal to 1 when the CEO is over the age of 60 years and 0 otherwise. All the variables except Restatement are measured one year prior to the year of the CEO turnover. We report the estimated coefficients from a logistic regression and the corresponding χ2–statistics in parenthesis.
** and * denote significance at the 1 percent and 5 percent level, respectively, for a two-tailed test.
31

32. Table 8
CEO Turnover and Losses: Two Stage Least Squares
First-Stage Regression
Second-Stage Regression
Dependent Variables =
Loss
Turnover
Intercept
-0.830 (38.42)**
-2.343 (157.68)**
-2.337 (68.81)**
Pred-Loss
0.648 (8.81)**
0.501 (4.15)*
Instruments
Cash-flow
-5.317 (354.37)**
Accrual
-2.726 (87.66)**
Sales-growth
-0.000 (0.05)
lag(Loss)
1.330 (400.62)**
Dividend
-0.678 (180.26)**
Dividend-stop
0.099 (0.52)
Governance variables
Board-size
0.024 (2.70)
Board-independence
0.000 (0.10)
CEO-Duality
-0.611 (92.21)**
Separate-committees
0.109 (1.64)
Ownership
-0.005 (1.66)
Control variables
Market-return
-0.346 (43.92)**
-0.340 (22.39)**
Asset-return
-0.368 (1.22)
-0.422 (0.89)
ΔEarnings
-0.113 (0.15)
-0.094 (0.04)
Stock-volatility
2.160 (10.76)**
1.836 (4.41)*
Earnings-volatility
-0.027 (0.01)
-0.310 (0.30)
Concentration
-0.572 (0.99)
-0.694 (0.86)
Size
-0.104 (49.08)**
0.089 (26.78)**
0.074 (8.26)**
Growth
-0.023 (1.30)
0.006 (0.04)
Restructure
0.141 (2.59)
0.222 (3.58)
Restatement
0.360 (21.88)**
0.398 (19.42)**
Age
0.629 (160.80)**
0.858 (180.25)**
Fixed effects
Industry and Year
Industry and Year
Industry and Year
Observations
18,190
11,228
7,184
Nagelkerke R2
32.71%
5.19%
7.87%
In the first stage regression, the dichotomous dependent variable Loss equals 1 when reported net income is negative in the current year and 0 otherwise. The instruments which are measured in the prior year are: Cash-flow is cash flows from operations divided by beginning period total assets, Accrual is total accruals (net income – cash flows from operations) divided by beginning period total assets, Sales-growth is the percentage growth in sales, lag(Loss) is the one-year lagged value of Loss, Dividend equals 1 when the firm pays dividends and 0 otherwise, and Dividend-stop is an indicator variable equal to 1 if the firm stopped paying dividends and 0 otherwise. In the second stage, we regress the dichotomous dependent variable Turnover which equals 1 for firms with CEO turnover on the estimated value of loss from the first stage regression (Pred-Loss). The governance and control variables are as follows. Board-size is the number of directors on the board. Board-independence is the percentage of independent directors on the board. CEO-duality and Separate-committees are indicator variables set to 1 when the CEO is also the board chair and when a firm has separate audit, nominating, and compensation committees, respectively. Ownership is the percentage of common stock held by the five top executives. Market-return is the difference between the raw returns and the value-weighted CRSP market returns over a twelve-month fiscal period. Asset- return is the industry-adjusted return on assets measured as the difference between the firm-specific and the industry-median income before extraordinary items deflated by total assets at the beginning of the year. ΔEarnings is the difference between current period earnings before extraordinary items and the corresponding number in the prior year deflated by market value of equity at the beginning of the year. Stock-volatility is the standard deviation of Market-return based on prior twenty-four monthly returns. Earnings-volatility is the standard deviation of Asset-return over the previous five years. Concentration is the industry level Herfindahl index. Size is the logarithmic
32

33. transformation of the fiscal year-end market value of equity. Growth is the sum of the market value of equity and the book value of debt scaled by the book value of total assets. Restructure is an indicator variable that equals 1 if special items as a percentage of total assets is less than or equal to -5 percent and 0 otherwise. Restatement is an indicator variable equal to 1 when a firm restates its financial statement in the current or prior year and 0 otherwise. Age is an indicator variable equal to 1 when the CEO is over the age of 60 years and 0 otherwise. All the control variables except Restatement in the second stage regression are measured one year prior to the year of the CEO turnover. We report the estimated coefficients from a logistic regression and the corresponding χ2–statistics in parenthesis.
** and * denote significance at the 1 percent and 5 percent level, respectively, for a two-tailed test.
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34. 34
Table 9
CEO Turnover and Magnitude of Losses
Dependent variable: Turnover
(1)
(2)
Intercept
-2.281 (171.92)**
-2.270 (168.25)**
Loss
0.459 (38.99)**
0.444 (32.30)**
Loss×Magnitude
0.609 (12.30)**
0.700 (8.66)**
Magnitude
-0.091 (0.31)
Control variables
Included
Included
Observations
11,738
11,738
Nagelkerke R2
6.26%
6.26%
The probability estimates of a CEO Turnover when firms report a loss. The dependent variable Turnover is an indicator variable that equals 1 when there is a change in the CEO in the current or subsequent year and 0 otherwise. Loss is an indicator variable with a value of 1 when net income is negative for the current year and 0 otherwise. Magnitude is the absolute value of net income deflated by book value of equity at the beginning of the year. The control variables are the same as those included in Table 3. We report the estimated coefficients from a logistic regression and the corresponding χ2–statistics in parenthesis.
** and * denote significance at the 1 percent and 5 percent level, respectively, for a two-tailed test.