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BANK MONITORING, FIRM PERFORMANCE, AND TOP MANAGEMENT TURNOVER IN JAPAN

Christopher W. Andersona, Terry L. Campbell IIb, Narayanan Jayaramanc, Gershon N. Mandelkerd

aSchool of Business, University of Kansas, Lawrence, KS 66045 bCollege of Business and Economics, University of Delaware, Newark, DE 19716

cDuPree College of Management,Georgia Institute of Technology, Atlanta, GA 30332 dKatz Graduate School of Business, University of Pittsburgh, Pittsburgh, PA 15260

Abstract

An inverse relation between performance and managerial turnover at Japanese firms suggests that bank monitoring substitutes for other governance mechanisms (Kaplan, 1994; Kang and Shivdasani, 1995). Morck and Nakamura (1999), however, report that Japanese banks protect their self-interests as creditors rather than the interests of shareholders when appointing corporate directors. We reexamine data on top management changes at Japanese firms and find results consistent with this latter notion. Specifically, management turnover is conditionally related to the ability to meet its short-term obligations rather than to profitability or stock returns. Bank monitoring is therefore not a substitute for mechanisms that directly serve shareholders’ interests.

JEL classification: G34 Keywords: Japanese firms; Managerial turnover; Corporate governance Corresponding author: Christopher Anderson KU School of Business

1300 Sunnyside Ave. Lawrence, KS 66045-7585, USA Tel: 785-864-7340 Email: cwanderson@ku.edu

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U.S.-style mechanisms for corporate control are relatively weak or non-existent in Japan.

For example, the ownership of many Japanese firms is characterized by cross holding of shares

by industrial and financial groups, and the market for takeovers is relatively inactive (Aoki, 1992;

Kester, 1991). Outside directorships are also rare in Japan (Ballon and Tomita, 1988; Kaplan,

1994), as are individual block holders (Nishiyama, 1984; Prowse, 1992). An inactive takeover

market, the prevalence of firm grouping, and the absence of individual block holders imply that

management is insulated from monitoring and control by shareholders (Nishiyama, 1984). On

the other hand, it has been argued that monitoring by commercial banks substitutes for

shareholder governance (Sheard, 1989; Aoki, 1990, 1992). Specifically, the intimacy of bank-

client relationships, coupled with the bank's authority to intervene during periods of financial

distress, may serve as a mechanism that monitors firm performance and disciplines management.

Kaplan (1994, 1997), Kaplan and Minton (1994), and Kang and Shivdasani (1995) report an

inverse relation between Japanese firm performance and managerial turnover that is seemingly

consistent with this notion.

Since the collapse of asset prices in Japan in the early 1990s, the ensuing recession, and

the onset of the banking crisis, the role of Japanese banks in the affairs of their client firms has

been critically reexamined. Kang and Stulz (2000) find that bank-dependent Japanese firms

experience worse stock price performance than other firms during the 1990s. Gibson (1995)

provides evidence that troubled Japanese banks inefficiently ration credit among their borrowers.

Kang, Shivdasani, and Yamada (2000) report that benefits to bank monitoring of investment

decisions by client firms appear to dissipate in the early 1990s when banks themselves became

troubled. Finally, Morck and Nakamura (1999) suggest that bank intervention by means of

appointments to boards of directors of client firms is in the short-term self-interest of the bank

rather than the interests of shareholders of such firms. These studies question whether monitoring

by Japanese banks effectively substitutes for mechanisms of corporate control that directly

safeguard shareholder wealth.

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The purpose of this study is to examine these two conflicting views of Japanese corporate

governance mechanisms by investigating the determinants of top management change.

Specifically, we investigate the extent to which measures that are directly related to creditors’

interest, such as liquidity and leverage, explain top management changes at Japanese firms as

opposed to profitability or stock returns. We examine data on top management changes and

performance at 207 Japanese firms from 1984 to 1989, a period that precedes the collapse of asset

prices and ensuing recession in the 1990s but which matches sample periods of earlier studies of

management incentives in Japan (Kaplan, 1994; Kang and Shivdasani, 1995). We first confirm

the findings of these earlier studies that report an inverse relation between profitability and

managerial turnover for similar sample periods. We then focus on measures of a firm’s ability to

meet its short-term obligations and the degree to which they predict top management changes.

Our findings suggest that firms with difficulties meeting short-term obligations display a higher

rate of top management change. Furthermore, we find that liquidity measures largely dominate

unconditional measures of profitability when examined simultaneously. Specifically, while

measures of liquidity and indebtedness are correlated with profitability, when we isolate

susceptibility to creditor monitoring in particular from poor earnings performance in general we

find that it is the former notion that matters most in influencing the likelihood of top management

changes. For example, independent of industry-adjusted earnings, firms with low interest

coverage ratios have significantly higher rates of top management change than firms with high

interest coverage ratios. In contrast, firms with high interest coverage ratios but with relatively

poor earnings performance display rates of managerial change similar to those of profitable firms.

These results suggest that top management change at Japanese firms is triggered specifically by

endangerment of creditors’ interests rather than poor profitability in general. Conversely,

managers of firms with sufficient liquidity to appease their creditors are not disciplined for poor

firm performance. Bank monitoring, therefore, does not substitute for other governance

mechanisms that directly safeguard the interests of shareholders. Instead, our findings are

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consistent with the hypothesis that the Japanese corporate governance system lacks mechanisms

that vigorously protect shareholder interests.

The remainder of this paper is organized as follows. Section I briefly reviews features of

the Japanese economy and their implications for corporate governance. Section II discusses our

data and methodology. Section III presents our results, and Section IV concludes.

I. Corporate Governance of Japanese Firms

Japanese corporations seem to lack several governance mechanisms that function in the

U.S. to mitigate problems associated with the separation of ownership from management. First,

large individual or family shareholders are rare in Japan (Prowse, 1992; Kaplan, 1994), and large

corporate shareholders, especially banks and insurance companies, are themselves diffusely held

(Nishiyama, 1984). Second, outside directors are observed relatively infrequently; Ballon and

Tomita (1988) claim that 43.5% of large Japanese companies have no outside directors, while

Kaplan (1994) cites 60% for his sample of 119 firms. Coupled with an absence of independent

corporate boards and powerful individual shareholders is an inactive takeover market.1 One

obstacle to takeovers among large Japanese firms is corporate grouping or keiretsu. A keiretsu is

a group of affiliated companies linked by crossholding of shares and the predominance of a

common large bank in the financial dealings of member firms. The stable cumulative

shareholdings of keiretsu members, including the so-called main bank, are large enough to render

hostile takeovers impossible (Aoki, 1990).

These features of the Japanese corporate system have led some observers to question

whether Japanese managers face any effective control mechanisms (Nishiyama, 1984). In

1 Kester (1991) describes the Japanese takeover market as confined to only small, privately negotiated

deals, with the purchase price for publicly announced mergers and acquisitions between 1982 and 1987

averaging less than the equivalent of $4 million.

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contrast, many authors cite the critical role played by banks in Japan and suggest that creditor

monitoring is an effective alternative mechanism that promotes corporate efficiency (Aoki, 1990,

1992; Sheard, 1989). Close ties between firms and banks may help resolve information

asymmetries and conflicts of interest between firms and suppliers of capital (Horiuchi, Packer and

Fukada, 1988; Prowse, 1990; Hoshi, Kashyap, and Scharfstein, 1990a, 1991), and provide an

efficient means for resolving financial distress (Suzuki and Wright, 1985; Hoshi, Kashyap, and

Scharfstein, 1990b). Most importantly, it is argued that monitoring by financial institutions

effectively substitutes for the missing takeover market as a mechanism to discipline top

management. In the case of keiretsu firms, for example, Sheard (1989) characterizes the main

bank as exploiting its informational assets derived from being a primary supplier of capital to the

firm to serve as a specialized monitor of managerial actions. In situations where corporate

performance is inadequate, the bank may intervene by stipulating policy adjustments, limiting

managerial discretion, lending managerial talent, and even calling for top management changes.2

Evidence on changes in Japanese boards of directors also suggests that banks place directors

representing their interest on corporate boards in response to poor performance (Kaplan and

Minton, 1994). Studies by Kaplan (1994, 1997) and Kang and Shivdasani (1995) find an inverse

relation between managerial turnover and stock returns or accounting income.3 On the basis of

this empirical relation, Kaplan and Ramseyer (1996) conclude that the notion of Japanese

managers acting without regard for shareholders is “another fable for the academy.”

The role of creditor monitoring in Japan, as discussed by Aoki (1990, 1992), for example ,

raises several questions regarding the extent to which monitoring by banks substitutes for

2 Pascale and Rohlen (1983) illustrate how such main bank intervention facilitated the turnaround of the

Mazda Corporation in the 1970s.

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mechanisms that directly protect shareholders’ welfare. First, performance benchmarks for

managers may be those that are of keen interest to creditors such as the firm's ability to meet its

interest and principal payment schedules. Second, the link between corporate performance and

top management change may be weak for firms performing above a certain threshold if only

firms in financial distress experience creditor-induced managerial turnover. Finally, firms with a

high exposure to creditor monitoring, i.e., firms which are highly leveraged in general and heavily

indebted to banks in particular, may display the strongest relation between performance and

turnover.

Morck and Nakamura (1999) test several implications of this perspective by examining

appointments of directors to Japanese boards. They report that appointments of directors by

banks are primarily related to the short-term interests of the bank, measured, for instance, by

liquidity. Kaplan and Minton (1994) suggest that such appointments presage executive turnover,

but Morck and Nakamura do not directly investigate management turnover. The objective of our

study is to examine the hypothesis that exposure to creditor monitoring triggered by poor liquidity

better predicts top management changes rather than unconditional corporate performance.

II. Sample and Data Description

We construct a sample of Japanese firms by cross-referencing Japanese company listings

in Moody's International with companies listed on the University of Rhode Island's Pacific Basin

Capital Markets Database (PACAP) for fiscal years from 1983 through 1989. This sample

comprises 207 firms, although for any year the number of firms represented is less than 207 due

to data deficiencies in Moody's. By nature of the selection criteria for coverage by Moody's, the

3 Popular press discussion of Japanese restructuring in the face of the most recent recession suggests that

Japanese stakeholders hold managers accountable for poor performance. See, for instance, The Wall Street

Journal, July 8, 1993, “Japanese CEOs Find Life is Getting Tougher at the Top.”

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sample firms are among the largest and best known firms in Japan. The sample contains many

firms that are smaller than the 119 firms composing the sample of a similar study by Kaplan

(1994). For fiscal year 1986, the 207 sample firms have mean (median) sales of $3.74 billion

($1.14 billion), total assets of $2.73 billion ($1.27 billion), and market value of equity of $2.06

billion ($1.22 billion).

A. Top Management Change

We identify executives with the title chairman, president, or chief executive officer as

listed in Moody's for 1983 through 1989. We classify the firm as having experienced top

management change if any previously listed top executive ceases to be listed as a top executive in

the following year.4 A mere shuffling of titles among executives without any executive ceasing

to be listed is not classified as a management change. This classification scheme is similar to that

of Warner, Watts, and Wruck (1988). The resulting sample of firm years totals 1,086

observations.

TABLE 1 ABOUT HERE

Table 1 reports management changes by year, industry, and keiretsu vs. non-keiretsu

classification. Panel A reports the frequency of management changes by fiscal year. The annual

frequency is relatively constant, with only 1986 having an unusually high number of management

changes. The average annual frequency of 13.4% is similar to the turnover frequencies reported

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for samples of U.S. firms by various authors as well as the 14.5% rate cited by Kaplan (1994) and

the 12.9% reported by Kang and Shivdasani (1995) for samples of Japanese firms. Panel B

demonstrates that the sample is well distributed across industry groups, but it also suggests

considerable industry variation in the incidence of top management change. Analysis of these

patterns rejects the hypothesis that turnover likelihood is identical across all industries. All

analyses were reproduced after including industry-specific dummy variables with results similar

to those reported. For brevity, further discussion of industry patterns is omitted. Panel C of

Table 1 compares top management changes in the keiretsu sample to that of the non-keiretsu firm

sample.5 The keiretsu and non-keiretsu firm samples comprise 69 and 138 firms, with 385 and

701 firm fiscal years, respectively. The rates of management change are similar (13.8% for

keiretsu members compared to 13.3% for non-keiretsu firms), and a chi-squared test fails to reject

the hypothesis that they are identical.

4 Lacking biographical data or the official reason for executive departure, our measure of management

change probably includes executive deaths in addition to departures and retirements. This biases against a

relation between firm performance and management change. Kaplan (1994) indicates that the annual rate

of executive death is less than 1%, or approximately about one out of every 15 observed top management

changes, so the effects are unlikely to be significant.

5 We utilize Nakatani (1984) to classify sample firms as keiretsu or non-keiretsu firms. Nakatani identifies

a firm as a keiretsu member if one of the following conditions is met: 1) a keiretsu's main bank has been the

largest lender to the firm for the prior three years and the equity share held by keiretsu member firms

exceeds 20%; 2) a keiretsu main bank has been the lender of at least 40% of the firm's debt for the prior

three years; 3) the firm has been historically identified as a member of a particular keiretsu. Nakatani also

provides a list of ostensibly independent firms. We identify only 18 sample firms (87 firm fiscal years) as

independent firms. The results do not differ significantly when we compare keiretsu firms to these

ostensibly independent firms.

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B. Firm Performance

We compute performance measures for sample firms using the PACAP Database for

Japan. First, we calculate return on assets (ROA), defined as earnings before interest and taxes

divided by total assets. We then subtract the equally-weighted matching industry average return

on assets from this measure for each observation and derive an industry-adjusted return on assets

referred to subsequently as IROA. Weisbach (1988), Barro and Barro (1990), and Kaplan (1994)

also use performance measures based on return on assets in studies concerning top management

incentives. We also compute profit margin on sales (IPM), defined as operating income scaled by

sales, adjusted by industry averages. Scaling earnings by sales may be more appropriate to the

extent that land and financial asset appreciation, accelerated depreciation, and other factors distort

book value of assets.

Stock returns are the performance measures of choice for a host of studies focusing on

U.S. firms (Coughlan and Schmidt, 1985; Warner, Watts, and Wruck, 1988; Jensen and Murphy,

1990; Gibbons and Murphy, 1990). We calculate a number of alternative stock return-based

performance measures, including raw returns, multiple-period cumulative raw returns, returns net

of value weighted or equally weighted return indices, and returns net of industry average returns.

Among these, the measures with the strongest relation to management changes are raw returns.

We report results using raw returns, cumulated over the two years prior to the observation year

(RET2) and the fours years prior to the observation year (RET4).

We examine whether variables that measure exposure to creditor pressure better explain

the incidence of top management change in Japan than profitability or stock returns. This

hypothesis is motivated by descriptive characterizations of Japanese corporate governance (e.g.,

Aoki, 1992) and the findings of Morck and Nakamura (1999) with respect to director

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appointments.6 We utilize several alternative measures of corporate liquidity and leverage. First,

we calculate the interest coverage ratio (COV) as operating income scaled by interest expense.

Hoshi, Kashyap, and Scharfstein (1990b) use such a measure as an indicator of financial distress.

We also compute a firm's quick ratio (QUICK) as current assets minus inventory divided by

current liabilities. The quick ratio is a stock measure of liquidity as opposed to a flow measure

such as the interest coverage ratio. We hypothesize that less liquid firms will experience higher

rates of management change.

In addition to these measures of liquidity, we also calculate two measures of leverage:

debt to firm value (DTV), defined as book value of debt divided by total firm value (market value

of equity plus book value of debt), and loans to value (LTV), defined as total loans outstanding

divided by firm value. Firms that have high leverage and especially high bank loan leverage are

more likely to be actively monitored by creditors (Hodder and Tschoegl, 1992; Aoki, 1992). In

contrast, less highly leveraged firms are unlikely candidates for active monitoring and direct

intervention.

TABLE 2 ABOUT HERE

TABLE 3 ABOUT HERE

Table 2 provides the means, medians, and standard deviations for these performance

variables, as well as for sales, total assets, and market value of equity. Table 3 reports

correlations among variables. As discussed above, the average size of sample firms is relatively

large, as mean (median) sales, assets, and market value of equity are 944 (282) billion yen, 534

6 Gilson (1989, 1990) also reports that financial distress tends to increase the likelihood of management

turnover at U.S. firms.

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(242) billion yen, and 422 (215) billion yen, respectively. Measures of earnings performance are

well behaved, with industry-adjusted return on assets (IROA) and profit margin (IPM) averaging

close to zero without excessively wide dispersion. The return measures presented (RET2 and

RET4) seem quite large (i.e., median return for the two prior years is 34.4%, median return for

the four prior years is 71.5%). However, given that our sample period includes the dramatic mid-

to-late 1980s rise in the Japanese stock market, the magnitude of these measures is not surprising.

Variables which proxy for exposure to creditor monitoring are also reasonably distributed with

the exception of interest coverage (COV), which has a skewed sample distribution due to a small

number of extreme, upper tail outliers. Due to the presence of these outliers (i.e., the 5% of the

observations with interest coverage ratios which exceed about 20), we set 20.0 as the upper limit

for the COV variable in all reported analyses. Not surprisingly, the four measures for creditor

monitoring are highly correlated as reported in Table 3.

III. Determinants of Top Management Change

We utilize the sample of firm-year management changes and corresponding firm

performance measures to estimate several permutations of a logit equation of the form:

ln{Pr(management change)/[1-Pr(management change)]} = a + X'B + e (1)

where Pr( . ) indicates probability, a is a scalar, X is a vector of performance measures and firm

characteristics, B is the corresponding vector of coefficients, and e is a zero mean error term. We

use maximum likelihood techniques to estimate (1) (see Judge, Griffiths, Hill, Lutkepohl, and

Lee, 1985). Results from an ordinary least squares estimation of a linear probability model are

similar to the reported logit results. To illustrate the economic significance of the estimated

coefficients from (1), we estimate the implied probability of top management change conditional

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on certain values of the independent variables via the following transformation of the estimated

form of (1):

Pr(management change / X) = exp( a + X'B ) / [ 1 + exp( a + X'B )] (2)

To gauge the economic significance of the estimated empirical relation we frequently calculate

the implied change in probability of top management change that results from a one standard

deviation change (plus or minus) in a performance measure from its mean.

TABLE 4 ABOUT HERE

A. Impact of Profitability and Stock Returns on Top Management Change

Table 4 presents estimated logit equations of top management change conditional on firm

performance as measured by return on assets, profit margin, and stock returns. The first two

columns of Table 4 provide estimated logit equations that explain the likelihood of top

management change as a function of industry adjusted return on assets (IROA) and industry

adjusted profit margin (IPM). These two measures are calculated for the fiscal year immediately

prior to the observation year. Similar results are obtained when observation-year measures are

used or when the measures are averaged across these two years. The results in these columns

indicate that top management changes in Japan are significantly related to earnings performance,

as the null hypotheses that management changes are unrelated to IROA or IPM is rejected at the

1% level. The estimated relations appear economically significant as well; the standardized

coefficient estimates imply that a one standard deviation increase (decrease) in IROA from the

sample mean results in a decrease (increase) in management change probability of 3.5% (4.6%)

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from the 12.9% rate predicted for a firm with mean IROA performance.7 The analogous

probabilities associated with a one standard deviation change in IPM from the mean are 4.0%

(5.5%) from a base level of 12.8% for a firm with mean IPM.

In order to gauge the fit of the estimated logit models and the economic significance of

the observed relation between performance and top management change, Table 5 presents actual

and estimated incidence of top management changes across performance quintiles. Panels A and

B of Table 5, for example, present the actual and predicted rates of top management change by

IROA and IPM quintiles. A comparison of actual and predicted rates of management change by

performance quintile indicates that the logit model estimations in columns (1) and (2) of Table 4

are not driven by outliers and, in fact, fit the data rather well. For IROA, the observed frequency

of management change increases monotonically as performance falls. For IPM, the relation is

nearly monotonic. Chi-squared tests for differences across performance quintiles confirm these

inferences. For both IROA and IPM, the incidence of top management change is significantly

different i) between the best performing quintile and the worst performing quintile, ii) between

firms with performance above the median and firms with below median performance, and iii)

across all performance quintiles. The observed and model-implied differences in the rate of

management changes between the best and worst performing firms are greater for IPM than for

IROA, perhaps implying that scaling earnings by annual sales captures relative performance

7 These probabilities are derived using equation (2) and the standardized coefficient estimates from Table 4

column (1). The predicted rate of management change for firms with mean IROA is calculated as

exp(-1.906)/[1+exp(-1.906)]=12.9%. The implied probability for a firm with a IROA one standard

deviation above the mean is exp(-1.906-0.359) / [1+exp(-1.906-0.359)]=9.4%. The implied probability for

a firm with IROA one standard deviation below the mean is exp(-1.906+0.359)/[1+exp(-

1.906+0.359)]=17.6%. Analogous calculations lead to the implied probabilities of management change

associated with variation in IPM.

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better than scaling by total assets, but the high degree of correlation between the variables

impedes further investigation of this question.

TABLE 5 ABOUT HERE

Columns (3) and (4) in Table 4 provide estimates of the relation between the likelihood

of top management change and stock return performance. In addition to raw returns cumulated

over the two-year (RET2) and four-year (RET4) periods preceding an observation year, we also

investigated market-adjusted returns, industry-adjusted returns, and multiple-year adjusted

returns. The only results that approach statistical significance are those for raw returns. In Table

4, for example, the coefficient estimate on raw returns cumulated over the four-year period prior

to an observation year (RET4) borders on statistical significance (p-value=10.5%). The

economic significance of the impact of stock returns on top management change is low, however.

The standardized coefficients on two-year returns (-0.111 as reported in column 3 of Table 4) and

four-year returns (-0.178 as reported in column 4) are smaller than the standardized coefficients

for the earnings based variables (e.g., -0.421 for IPM as reported in column 2). This implies that

a one standard deviation change in stock return has a much smaller impact on probability of top

management change than a one standard deviation change in IROA or IPM. Second, when we

examine observed top management change across performance quintiles based on RET2 and

RET4 (panels C and D of Table 5) we find that the differences in rates of management change

across quintiles are narrow, prone to non-monotonicities, and, with the exception of the above

versus below median performance test for RET4 in panel D, statistically insignificant. Third,

when we include both an earnings based measure of performance and a stock return based

measure of performance (columns (5)-(8) of Table 4), estimated coefficients on stock return

measures, although of the hypothesized sign, are smaller in magnitude and are statistically

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indistinguishable from zero. In short, we find little evidence in support of a relation between

stock returns and top management change.

These results on stock returns seem at first to contrast with those of Kaplan (1994) and

Kang and Shivdasani (1995), who find a significant relation between top management change and

raw stock returns for different samples of Japanese firms. However, upon closer examination are

results can be reconciled. First, Kaplan's sample is composed of the largest 119 Japanese firms

with average annual sales of $5.6 ($3.5) billion, while our sample comprises 207 firms with mean

(median) annual sales of $3.7 ($1.1) billion. When we restrict our sample to include only the

largest 119 firms in any given year or only firms with above sample medium sales, we find that

the coefficient on RET4, which borders on conventional significance in Table 4, becomes

statistically significant at the 10% level. Second, our results are consistent with Kaplan’s in that

only earnings-based variables have robust explanatory power. Specifically, in both Kaplan’s

tables and ours the magnitude of the coefficients on earnings variables is much larger than that for

stock return variables. Furthermore, Kaplan finds that stock returns are not significant in a

multivariate framework in which earnings variables are also included. This latter finding is

consistent with columns (5)-(8) of Table 4. Finally, differences in definitions of turnover and

sample construction partially explain the difference in results. Kaplan finds a significant relation

between top management change and stock returns for a very narrow definition of top

management change - instances where a Japanese president ceases to be president yet does not

assume the chairmanship, a category that contains only about one fourth of all of Kaplan's

observations of top management change. When Kaplan utilizes a broader definition of turnover,

top executive change is not significantly related to stock returns. Our definition of top

management change is more refined than Kaplan's broad definition, yet not as restrictive as the

"president does not become chairman" definition. For example, our definition does not include

instances where chairman/president relinquishes the presidency to a newcomer but keeps the

chairmanship; Kaplan's broad definition regards this as turnover, his narrow definition does not.

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In short, while we can replicate Kaplan's finding regarding stock returns on a restricted sample of

larger firms and using a particular return measure, our conclusion is that stock returns have

marginal explanatory power when compared to earnings-based measures of performance.

Kang and Shivdasani (1995) suggest that the weak relation between returns and top

management change may be partially due to imperfections in identification of the turnover year

due to reliance on Moody’s or failure to distinguish between routine and non-routine managerial

turnover. These suggestions do not explain, however, why we fail to find economic and

statistical significance for stock returns yet find significant results for accounting-based measures.

Second, while we consider a departing chairman succeeded by a sitting president as top

management change, we do not identify a situation where a chair/president relinquishes only the

latter title as a management change. Consequently, the routine versus non-routine distinction

made by Kang and Shivdasani is somewhat, but not fully, reflected in our definition of

management change. Finally, Kang and Shivdasani themselves do not report multivariate results.

We suspect that such analysis would confirm our finding that the role of earnings-based measures

dwarfs that of stock returns.

Finally, the weak relation between stock returns and management change could be

peculiar to our sample period. Japanese security prices increased rapidly without parallel growth

in earnings during the late 1980s. Consequently, stock returns were imprecise indicators of

managerial performance during this period. This characterization of stock return performance as

a relatively noisy indicator of managerial effort and decision-making quality may explain the

important role seemingly assumed by accounting measures such as industry adjusted return on

assets or profit margin. This explanation is consistent with Lambert and Larcker (1987), who

find that the relative importance of stock returns versus accounting measures in evaluating and

rewarding managerial performance in the U.S. is positively related to the degree to which such

measures are likely to be informative about managerial actions. In a similar vein, Jarrell and

Dorkey (1992) find that accounting measures of performance tend to be highly correlated with

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long-run stock return performance. They argue for the use of such measures in managerial

incentives because they are less likely to be affected by macroeconomic “noise” such as that

coincident with the extraordinary run-up of Japanese stock prices in the late 1980s.

B. Top Management Change and Exposure to Creditor Monitoring

The prior section finds a relation between firm performance, especially when measured

by accounting income, and managerial change. This finding is comparable to those of Kaplan

(1994) and Kang and Shivdasani (1995). As discussed in Section II, bank intervention during

periods of poor performance may be a unique and effective governance mechanism in the

Japanese economy. Since active creditor monitoring and intervention are most likely to occur

when firms are highly indebted or experiencing severe liquidity problems, we next estimate the

likelihood of top management change as a function of alternative measures of liquidity and

leverage.

TABLE 6 ABOUT HERE

Table 6 presents estimated logit equations of top management change conditional on

variables that proxy for exposure to creditor monitoring: interest coverage (COV), quick ratio

(QUICK), debt to value (DTV), and loans to value (LTV). Each coefficient has the hypothesized

sign and is statistically significant in the univariate equation estimates reported in columns (1)-(4)

of Table 6. The standardized coefficient estimates are all of a magnitude comparable to those for

accounting performance variables in Table 4. For example, a one standard deviation increase

(decrease) in COV results in an decreased (increased) probability of top management change of

4.2% (5.8%) from the 12.7% rate of top management change for firms with mean coverage

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ratios.8 The multivariate equation estimates provided in columns (5) and (6) suggest that the

interest coverage ratio (COV) is the most important of these variables, as the debt to value and

loan to value coefficients are insignificant when COV enters the equation. When either debt to

value (DTV) or loans to value (LTV) enter the estimated equations, QUICK is rendered

insignificant (columns (7) and (8)).

TABLE 7 ABOUT HERE

Table 7 reports predicted and observed frequency of top management change across

sample quintiles based on liquidity and leverage. The actual incidence of top management

change is significantly related to each of the four variables examined. Interest coverage (COV -

panel A) is a particularly interesting variable. Firms in the highest coverage quintile have annual

management change of just 6.9%, while firms in the middle three quintiles have turnover rates

that are close to the unconditional mean, and firms in the lowest coverage display an annual top

management change rate of 18.9%. A similar pattern across quintiles is evident for debt to value

(DTV) in panel C. The results for quick ratio (QUICK-panel B) indicate some non-

monotonicities in top management change with respect to this variable and a relatively poor

model fit in comparison to the other variables. Loans to value (LTV-panel D) displays a similar

non-monotonicity, but only for the second quintile.

The results in Table 6 and Table 7 suggest that changes in Japanese top management are

significantly related to measures of liquidity and indebtedness. This suggests that creditor

monitoring is the mechanism that disciplines top management. However, the evidence presented

thus far does not distinguish creditor monitoring per se from a simple hypothesis of performance-

8 These implied probabilities are derived from equation (2) using the standardized coefficient estimates

from column (1) of Table 6. An example of such a calculation is presented in footnote 7.

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related managerial turnover. For example, while there is an empirical relation between

alternative measures of leverage and observed top management change, these measures are

correlated with earnings performance (see Table 3). The relation between interest coverage and

alternative measures of corporate earnings such as IROA and IPM is obvious, but the other

leverage measures are also highly correlated with corporate profitability (see Table 3). Prowse

(1990), for example, documents that leverage for Japanese firms is negatively related to past

profitability. Consequently, the results attributed to earnings performance per se may actually be

due to exposure to creditor monitoring, or the reverse. Furthermore, discussions of creditor

monitoring in Japan suggest that management is subject to active monitoring and potential

discipline in times of financial distress. To further investigate the creditor-monitoring hypothesis,

we segment the sample by both firm profitability (measured by IROA and IPM) and exposure to

creditor monitoring (measured by COV, QUICK, DTV and LTV). Specifically, in Table 8 we

divide the sample into quadrants based on the median profitability and median liquidity or

leverage and investigate top management change across the resulting four quadrants. Similar

analyses were conducted using return-based measures; consistent with our findings in Tables 4

and 5, conditioning top management change on the basis of returns had no meaningful effect.

TABLE 8 ABOUT HERE

Panels A and B of Table 8 present persuasive evidence that it is exposure to creditor

monitoring per se and not mere earnings performance that influences top management change in

Japan. Panel A breaks the sample into four quadrants based on industry-adjusted return on assets

(IROA) and interest coverage (COV). These two measures are highly correlated (their correlation

coefficient, reported in Table 3, is 0.69), yet there are still many observations with above median

IROA yet below median interest rate coverage (n=142). Similarly, there are 142 firm-years with

below median IROA and above median coverage. For firms with above median coverage

19

(COV=high) there is no significant difference in the incidence of top management change for

firms with above median IROA (top management change of 38/401=9.5%) and firms with below

median IROA (top management change of 15/142=10.6%). Similarly, for firms with below

median coverage ratios, there is no significant difference in top management change with respect

to IROA classification (above median rate of 21/142=14.8%, below median rate of 18.0%, chi-

squared statistic insignificant at 0.76). However, firms with above median IROA but below

median coverage have a significantly higher rate of managerial change than firms with high

IROA and high coverage (14.8% versus 9.5%, chi-squared of 2.89). Similarly, firms with low

coverage and low IROA have significantly more management changes than firms with high

coverage and low IROA (18.0% versus 10.6%, chi-squared of 4.58). The results using industry-

adjusted profit margin (IPM) to split the sample (panel B) parallel those of panel A. After

controlling for coverage there is no significant difference in management change by IPM, yet

after controlling for IPM there are significant differences by interest coverage. These results

suggest that top management change in Japanese firms is related to exposure to creditor

monitoring, measured by interest coverage, and not to unconditional earnings performance.

These findings buttress results from Kang and Shivdasani (1995), who report that negative

income (and presumably negative cash flow and interest coverage) dramatically raises the odds of

turnover, not merely below average performance.9 Panels C and D of Table 8, which present

results based on segmenting the sample by quick ratio and, alternatively, IROA and IPM, provide

further evidence in support of creditor monitoring. First, firms with high levels of asset liquidity,

i.e., above median quick ratios, display significantly more management changes when

profitability is low (13.5% versus 7.7%, chi-square of 4.64, in panel C; 13.2% versus 7.6%, chi-

9 In Kang and Shivdasani’s Table 6 turnover for negative income firm years is 13% for firms with bank ties

and 8.3% for firms without such ties compared to 1.2% and 2.9%, respectively, for firm years with positive

income.

20

square of 4.58, in panel D). However, the differences are even larger when high profit margin

liquid firms are compared to high profit illiquid (i.e., low quick ratio) firms (7.7% versus 16.7%

in panel C; 7.6% versus 15.6% in panel D). This suggests that a firm's ability to meet its short-

term obligations is at least as important as relative profitability in influencing top management

change. Not surprisingly, the worst possible quadrant, the one associated with low quick ratio

and low profitability, displays the highest rate of top management change (17.4% in panel C;

18.1% in panel D), but for firms with poor profitability turnover does not significantly increase

when QUICK is below median.

Panels E-H of Table 8 suggest that the relation between profitability and top management

change is not conditional on aggregate leverage or bank leverage. In all four panels, high

performance, low leverage firms display the lowest rates of managerial change. However,

management changes increase when performance declines for both high and low leverage

samples, although these differences are not always significant. These results do not suggest that

high leverage firms have a stronger turnover-performance relation than less leveraged firms. We

also estimate logit equations with the leverage measures, performance measures, and interaction

terms as independent variables. Consistent with the breakdown in Table 8, we find that estimated

coefficients on the leverage measures and performance measures are statistically significant, but

that the coefficients on the interactions of these variables are not. For brevity we omit these

results.

In general, the results reported in Table 6, Table 7, and Table 8 indicate that liquidity

variables significantly affect the level of top management change at Japanese firms. In particular,

low interest coverage ratios seem more important in explaining top management change than

return of assets or profit margin. Specifically, firms with below median coverage ratios have

significantly higher rates of top management change regardless of industry-adjusted profitability.

A similar result holds when we measure liquidity with the firm’s quick ratio. On the other hand,

top management change is not significantly higher for firms with below median profitability but

21

relatively high coverage ratios compared to firms with above median profitability. These results

suggest that management change occurs disproportionately more often when the interests of

creditors are threatened and not when firms perform poorly yet have sufficient cash to appease

creditors.

C. Additional Results on Keiretsu Firms Versus Non-keiretsu Firms

The role of Japanese banks in monitoring client firms and intervening in times of

financial distress is often hypothesized to be especially pronounced for members of keiretsu

corporate groups. The long-standing ties between lenders and borrowers, extraordinary bank

access to information on the borrower, and implicit control rights afforded the so-called main

bank under extraordinary circumstances suggest that creditor monitoring is more likely to

influence top management change for keiretsu member firms. To test this implication we conduct

a logit estimation of top management change with a keiretsu dummy variable intercept and an

interactive dummy on measures of performance, liquidity, and indebtedness. A negative

coefficient estimate for the interactive term would imply that keiretsu member firms display top

management change that is more sensitive to firm performance. The keiretsu specific intercept

term is not significantly different from zero in all specifications, confirming the prima facie

evidence in Table 1 that the incidence of managerial change is identical for keiretsu and non-

keiretsu firms. The coefficients on interactive dummy variables are also insignificant for all

specifications, suggesting that the turnover-performance relations documented earlier do not vary

by keiretsu affiliation. The strongest statement we can make about differential sensitivity of

management changes to performance concerns four-year cumulative stock returns (RET4): the

relation between top management change and stock returns is significantly negative for keiretsu

firms and insignificantly negative for non-member firms, but this difference itself is not

significant. This findings are similar to that reported by Morck and Nakamura (1999) with

respect to bank appointments to boards of directors. Additional specifications, involving

22

alternative variables and interactions of variables, also failed to distinguish keiretsu from non-

member firms. Consequently, we find no evidence that the relation between top management

change and Japanese firm performance differs by keiretsu affiliation. For brevity, we omit full

reporting of these results.

IV. Summary and Conclusions

Recent empirical findings of an inverse relation between firm performance and

managerial turnover at Japanese firms are construed as evidence that bank monitoring substitutes

for other corporate governance mechanisms (Kaplan, 1994; Kang and Shivdasani, 1995). In

contrast, Morck and Nakamura (1999) report that banks act to protect their narrow self-interest as

creditors when appointing corporate directors rather than the interests of shareholders. We

examine these conflicting views by investigating the extent to which top management changes at

Japanese firms are explained by measures of liquidity and leverage that are of direct concern to

creditors as opposed to measures of interest to shareholders such as profitability or stock returns.

Specifically, we examine the relation between top management change and profitability, stock-

price performance, and variables that reflect a firm’s ability to meet its short-term obligations for

a sample of 207 Japanese firms in the 1980s.

First, we find that top management changes are significantly related to accounting

measures of firm performance but are less sensitive to stock-price performance measures. These

results are consistent with evidence on the performance-turnover relation as reported by Kaplan

(1994) and Kang and Shivdasani (1995). Next, we find that top management changes are

significantly related to measures of liquidity and leverage, and these measures largely dominate

profitability per se. For instance, we investigate management changes for firms with high (low)

industry adjusted rates of profitability but differential exposure to potential creditor monitoring as

measured by liquidity and leverage variables. Firms with high industry-adjusted profitability but

with low liquidity experience significantly higher rates of management change than similarly

23

profitable yet liquid firms. Similarly, relatively unprofitable yet liquid firms have fewer

management changes than other unprofitable firms. In short, liquidity measures of keen interest

to creditors seem to drive top management changes to a greater degree than earnings or stock

return performance. Consistent with the evidence on appointments to corporate boards reported

by Morck and Nakamura (1999), our findings counter prior inferences that a performance-

turnover relation is evidence of effective corporate governance by means of bank monitoring

(Kaplan, 1994; Kang and Shivdasani, 1995; Kaplan and Ramseyer, 1996). Instead, Japanese

corporate governance mechanisms appear skewed to protect creditors’ interests rather than those

of shareholders. Specifically, our results suggest that monitoring by creditors is driven by their

own short-term interests and is therefore an imperfect substitute for other mechanisms of

corporate control that directly protect the interests of shareholders of Japanese firms.

24

Acknowledgements

We are grateful for the comments and suggestions on previous incarnations of this study. In

particular, we thank Peter Abken, Mark Hirschey, Chuan Yang Hwang, Jonathon Karpoff, Ken

Lehn, Anil Makhija, Bob Nachtmann, David Nachman, Tom Noe, Steve Smith, Larry Wall,

Jerold Warner, and workshop participants at the University of Pittsburgh and Georgia Tech.

25

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Table 1. Observed Frequency of Top Management Change1 Fiscal-year Management Annual Observations Changes Frequency A. By fiscal year 1984 164 19 11.6% 1985 181 20 11.0% 1986 186 36 19.4% 1987 185 25 13.5% 1988 189 26 13.8% 1989 181 20 11.0% All years 1,086 146 13.4% B. By industry Textiles 63 9 14.3% Pulp & paper 35 6 17.1% Chemicals 168 22 13.1% Petroleum & rubber 23 2 8.7% Glass & ceramics 42 10 23.8% Iron & steel 34 5 14.7% Other metals 47 8 17.0% Machinery 108 10 9.3% Electrical machinery 173 25 14.5% Transportation equipment 112 17 15.2% Precision equipment 52 6 11.5% Other manufacturing 72 2 2.8% Wholesale 50 11 22.0% Retail 79 6 7.6% Transportation & shipping 28 7 25.0% C. By keiretsu classification Keiretsu (69 firms) 385 53 13.8% Non-keiretsu (138 firms) 701 93 13.3% 1Note: This table reports observed managerial change for 207 firms composing a sample of 1,086 fiscal years from 1984 to 1989. Management change is defined as the delisting of any top executives (chairman, president, or CEO) previously listed as such by Moody’s International. The number of observations per fiscal year reported in panel A varies according to data availability for sample firms in Moody’s. Industry classification for panel B is according to the PACAP Database for Japan. Keiretsu classification in panel C is by Nakatani (1984).

31

Table 2. Summary Statistics for Firm-specific Variables1 Variable Mean Median Std. dev. Sales (Yen billion) 944 282 2,429 Assets (Yen billion) 534 242 802 Market Value Equity (Yen billion) 422 215 589 ROA - return on assets 0.079 0.071 0.041 IROA - industry adjusted return on assets 0.009 0.003 0.037 PM - profit margin on sales 0.057 0.050 0.053 IPM - industry adjusted profit margin 0.010 0.004 0.048 RET2 - stock return, prior two years 0.488 0.344 0.673 RET4 - stock return, prior four years 1.057 0.715 1.357 *COV - operating income to interest expense 6.287* 3.642 6.103*

QUICK - current assets minus inventory to 1.311 1.039 0.876 current liabilities DTV - total debt to value (debt + market equity) 0.428 0.399 0.216 LTV - loans to value (debt + market equity) 0.143 0.087 0.156 1Note: This table provides the mean, median, and standard deviation of key variables for a sample of 1,086 fiscal years from 207 firms over 1984-1989. All data is from the PACAP Database for Japan. Industry adjusted variables are calculated by subtracting the fiscal-year industry mean value of a given variable from the raw value. Industry classification is by the PACAP two-digit code and the entire PACAP universe of firms is sampled to derive industry means.

*To reduce distortions by extreme outliers, interest coverage observations above the 5% tail of the distribution have been set to the 95% level of the distribution, or about 20.0. Without truncation the mean and standard deviation of COV are 128.3 and 1050.9, respectively.

32

Table 3. Correlation Matrix for Firm-Specific Variables

Sales Assets MVE ROA IROA PM IPM RET2 RET4 COV QUIK DTV LTV

Sales … 0.736 0.298 -0.098 -0.065 -0.197 -0.133 -0.054 -0.068 -0.120 -0.107 0.311 0.228

Assets 0.736 … 0.588 -0.153 -0.092 -0.191 -0.126 -0.032 -0.059 -0.179 -0.188 0.372 0.284

MVE 0.298 0.588 … 0.119 0.157 0.086 0.083 0.188 0.217 0.152 -0.014 -0.217 -0.191

ROA -0.098 -0.153 0.119 … 0.941 0.806 0.773 0.170 0.288 0.722 0.305 -0.529 -0.411

IROA -0.065 -0.092 0.157 0.941 … 0.778 0.820 0.135 0.255 0.693 0.360 -0.504 -0.376

PM -0.197 -0.191 0.086 0.806 0.778 … 0.955 0.208 0.318 0.593 0.376 -0.497 -0.330

IPM -0.133 -0.126 0.083 0.773 0.820 0.955 … 0.164 0.278 0.572 0.388 -0.423 -0.265

RET2 -0.054 -0.032 0.188 0.170 0.135 0.208 0.164 … 0.720 0.105 -0.081 -0.233 -0.063

RET4 -0.068 -0.059 0.217 0.288 0.255 0.318 0.278 0.720 … 0.163 -0.044 -0.319 -0.132

COV -0.120 -0.179 0.152 0.722 0.693 0.593 0.572 0.105 0.163 … 0.566 -0.686 -0.619

QUIK -0.107 -0.188 -0.014 0.305 0.360 0.376 0.388 -0.081 -0.044 0.566 … -0.515 -0.457

DTV 0.311 0.372 -0.217 -0.529 -0.504 -0.497 -0.423 -0.233 -0.319 -0.686 -0.515 … 0.842

LTV 0.228 0.284 -0.191 -0.411 -0.376 -0.330 -0.265 -0.063 -0.132 -0.619 -0.457 0.842 …

33

Table 4. Likelihood of Top Management Change Based on Profitability and Stock Returns1 Variable (1) (2) (3) (4) (5) (6) (7) (8) INTERCEPT -1.821 -1.830 -1.787 -1.716 -1.780 -1.743 -1.799 -1.768 [-1.906] [-1.919] [-1.867] [-1.855] [-1.907] [-1.887] [-1.921] [-1.90] (0.0000) (0.0000) (0.0000) (0.0000) (0.0000) (0.0000) (0.0000) (0.0000) IROA -9.612 … … … -9.341 -8.776 … …(industry adjusted [-0.359] [-0.347] [-0.324]return on assets) (0.0004) (0.0007) (0.0019) IPM … -8.832 … … … … -8.760 -8.400(industry adjusted [-0.421] [-0.418] [-0.398]profit margin) (0.0001) (0.0001) (0.0002) RET2 … … -0.164 … -0.097 … -0.071 …(stock return, [-0.111] [-0.065] [-0.048]year t-2 to t-1) (0.2544) (0.5037) (0.6303) RET4 … … … -0.131 … -0.068 … -0.049(stock return, [-0.178] [-0.092] [-0.067]year t-4 to t-1) (0.1049) (0.3957) (0.5355) Chi-squared 13.53 17.67 1.37 3.01 13.78 13.30 18.21 17.56(p-value) (0.0002) (0.0000) (0.2411) (0.0826) (0.0010) (0.0013) (0.0001) (0.0002) Observations 1,086 1,086 1,079 1,062 1,079 1,062 1,079 1,062

1Note: This table presents estimated logit equations where the dependent variable is equal to one when a top executive (chairman, president, or CEO) as reported by Moody's International ceases to be listed over 1984-1989. Independent variables are: IROA - industry adjusted return on assets in the prior fiscal year; IPM - industry adjusted profit margin on sales in the prior fiscal year; RET2 - cumulative stock return in the two years prior to the current fiscal year; and RET4 - cumulative stock return over the four prior years. Numbers in square brackets are the coefficients on standardized independent variables. Numbers in parentheses are p-values associated with t-tests of the coefficient estimates.

34

Table 5. Predicted and Observed Managerial Change Based on Profitability and Stock Returns1

A. Management change conditional on IROA B. Management change conditional on IPM

IROA Quintile IPM Quintile Quintile Median Predicted Observed Quintile Median Predicted Observed

high 0.049 9.2% 10.1% high 0.058 8.8% 6.4%2 0.019 11.9% 10.6% 2 0.022 11.7% 13.4%3 0.003 13.5% 13.4% 3 0.004 13.4% 12.4%4 -0.009 15.0% 15.2% 4 -0.011 15.0% 16.1%

low -0.026 17.2% 18.0% low -0.030 17.3% 18.9%

Chi-squared tests of observed turnover Chi-squared tests of observed turnover high quintile=low: 5.67 ** high quintile=low: 15.91 ***

above median=below: 6.24 ** above median=below: 6.93 ***high=2=3=4=low: 7.96 * high=2=3=4=low: 17.62 ***

C. Management change conditional on RET2 D. Management change conditional on RET4

RET2 Quintile RET4 Quintile Quintile Median Predicted Observed Quintile Median Predicted Observed

high 1.264 12.0% 11.1% high 2.520 11.4% 11.7%2 0.656 13.1% 11.6% 2 1.226 13.3% 11.8%3 0.344 13.7% 16.7% 3 0.715 14.1% 12.2%4 0.093 14.2% 15.8% 4 0.329 14.7% 17.0%

low -0.147 14.6% 12.0% low -0.040 15.3% 15.6%

Chi-squared tests of observed turnover Chi-squared tests of observed turnover high quintile=low: 0.09 high quintile=low: 1.33

above median=below: 1.32 above median=below: 3.53 *high=2=3=4=low: 4.92 high=2=3=4=low: 4.23

***,**,* significantly different from zero at the 1%, 5%, and 10% levels, respectively.

Management Change Management Change

Management Change Management Change

1Note: Each panel displays the sample distribution of a performance measure and turnover probabilities across performance quintiles. Performance measures are: IROA - industry adjusted return on assets in prior fiscal year; IPM – industry adjusted profit margin on sales in prior fiscal year; RET2 - cumulative stock return in the two prior fiscal years; RET4 - cumulative stock return over the four prior fiscal years. Predicted turnover is obtained by using the estimated logit equations in Table 4 conditional on quintile median performance. Tests statistics for differences in observed turnover rates are chi-squared tests with one, one, and four degrees of freedom, respectively.

35

Table 6. Likelihood of Top Management Change Based on Liquidity and Leverage1 Variable (1) (2) (3) (4) (5) (6) (7) (8) INTERCEPT -1.471 -1.427 -2.516 -2.117 -1.786 -1.552 -2.191 -1.769 [-1.928] [-1.893] [-1.898] [-1.886] [-1.928] [-1.926] [-1.915] [-1.898] (0.0000) (0.0000) (0.0000) (0.0000) (0.0000) (0.0000) (0.0000) (0.0000) COV -0.073 … … … -0.058 -0.067 … …(operating income [-0.444] [-.356] [-0.407]over interest) (0.0001) (0.0141) (0.0035) QUICK … -0.355 … … … … -0.162 -0.223(current assets - inv. [-0.311] [-0.142] [-0.196]to current liabilities) (0.0105) (0.2809) (0.1309) DTV … … 1.444 … 0.524 … 1.165 …(total book debt [0.312] [0.113] [0.252]to firm value) (0.0003) (0.3319) (0.0140) LTV … … … 1.615 … 0.310 … 1.149(total loans [0.251] [0.048] [0.179]to value) (0.0022) (0.6493) (0.0588) Chi-squared 18.27 8.08 12.78 8.95 19.21 18.48 14.05 11.55(p-value) (0.0000) (0.0045) (0.0003) (0.0028) (0.0001) (0.0001) (0.0009) (0.0031) Observations 1,086 1,086 1,086 1,086 1,086 1,086 1,086 1,086

1Note: This table presents estimated logit equations where the dependent variable is equal to one when a top executive (chairman, president, or CEO) listed by Moody's International ceases to be listed over 1984-1989. Independent variables are: COV - ratio of operating income divided by interest expense; DTV - total book value of debt divided by sum of book debt and market value of equity; LTV - book value of loans divided by sum of book debt and market value of equity; QUICK - total current assets minus inventory divided by total current liabilities. To improve model fit and reduce the influence of extreme outliers, COV observations above the upper 5% tail have been set to the 95% level of the distribution. Numbers in square brackets are the coefficients on standardized independent variables. Numbers in parentheses are p-values associated with t-tests of the coefficient estimates.

36

Table 7. Predicted and Observed Managerial Change Based on Liquidity and Leverage1

A. Management change conditional on COV B. Management change conditional on QUICK

COV Quintile QUICK Quintile Quintile Median Predicted Observed Quintile Median Predicted Observed

high 18.770 5.6% 6.9% high 2.283 9.6% 9.2%2 7.100 12.1% 12.4% 2 1.363 12.9% 7.8%3 3.640 15.0% 14.4% 3 1.039 14.2% 17.5%4 2.040 16.5% 14.7% 4 0.835 15.1% 16.1%

low 1.240 17.4% 18.9% low 0.634 16.1% 16.6%

Chi-squared tests of observed turnover Chi-squared tests of observed turnoverhigh quintile=low: 14.47 *** high quintile=low: 4.62 **

above median=below: 12.80 *** above median=below: 12.80 ***high=2=3=4=low: 15.21 *** high=2=3=4=low: 16.41 ***

C. Management change conditional on DTV D. Management change conditional on LTV

DTV Quintile LTV Quintile Quintile Median Predicted Observed Quintile Median Predicted Observed

low 0.166 9.3% 7.4% low 0.000 10.8% 10.6%2 0.286 10.9% 12.0% 2 0.028 11.2% 9.7%3 0.399 12.6% 13.8% 3 0.087 12.2% 12.9%4 0.534 14.9% 14.3% 4 0.181 13.9% 15.2%

high 0.747 19.2% 19.7% high 0.398 18.6% 18.8%

Chi-squared tests of observed turnover Chi-squared tests of observed turnoverhigh quintile=low: 14.63 *** high quintile=low: 5.91 **

above median=below: 5.37 ** above median=below: 4.58 **low=2=3=4=high: 15.2 *** low=2=3=4=high: 10.00 **

Management Change Management Change

Management Change Management Change

1Note: Each panel displays the sample distribution of a performance measure and turnover probabilities across quintiles for measures of liquidity and indebtedness. Measures are: COV - ratio of operating income divided by interest expense; DTV - total book value of debt divided by sum of book debt and market value of equity; LTV - book value of loans divided by sum of book debt and market value of equity; QUICK - total current assets minus inventory divided by total current liabilities. Predicted turnover is obtained by using the estimated logit equations in Table 6 conditional on quintile median performance. Tests statistics for differences in observed turnover rates are chi-squared tests with one, one, and four degrees of freedom, respectively.

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Table 8. Management Change Based on Exposure to Creditor Monitoring versus Profitability1

A. IROA x COV Quadrants B. IPM x COV Quadrants

COV COVhigh low chi-squared high low chi-squared

high 9.5% 14.8% 2.89 high 8.9% 14.3% 3.59 IROA (38/401) (21/142) {0.0894} IPM (32/361) (26 /182) {0.0583}

low 10.6% 18.0% 4.58 low 11.5% 18.6% 4.61(15/142) (72 /401) {0.0323} (21/182) ( 67/361) {0.0319}

chi-squared 0.14 0.76 chi-squared 0.96 1.60{0.7097} {0.3835} {0.3273} {0.2065}

C. IROA x QUICK Quadrants D. IPM x QUICK Quadrants

QUICK QUICKhigh low chi-squared high low chi-squared

high 7.7% 16.7% 9.86 high 7.6% 15.6% 8.46 IROA (27/351) (32/192) {0.0017} IPM (25/331) (33/212) {0.0036}

low 13.5% 17.4% 1.39 low 13.2% 18.1% 2.35(26/192) (61/351) {0.2388} (28/212) (60/331) {0.1250}

chi-squared 4.64 0.04 chi-squared 4.58 0.60{0.0312} {0.8329} {0.0324} {0.4375}

1Note: The table provides incidence of top management change based on measures of profitability, liquidity, and leverage. Each panel splits the sample of 1,086 observations into four quadrants based on a measure of profitability, industry-adjusted return on assets (IROA) or industry-adjusted profit margin (IPM), and then by measures of liquidity or indebtedness, i.e., interest coverage ratio (COV), quick ratio (QUICK), debt to value ratio (DTV), or loans to value ratio (LTV). The notation "high" and "low" denotes above median and below median, respectively. The rate of top management change per quadrant, the number of instances of and sample size per quadrant (in parentheses), and chi-squared tests for equality of turnover frequency across selected quadrants are provided. P-values for the chi-squared statistics are presented in scrolled brackets.

(continued)

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Table 8. (continued) E. IROA x DTV Quadrants F. IPM x DTV Quadrants

DTV DTVlow high chi-squared low high chi-squared

high 9.4% 14.0% 2.49 high 9.4% 13.2% 1.75 IROA (35/372) (24/171) {0.1145} IPM (34/361) (24/182) {0.1859}

low 14.6% 16.7% 0.37 low 14.3% 17.2% 0.76(25/171) (62/372) {0.5432} (26/182) (62/361) {0.3844}

chi-square 3.10 0.62 chi-square 2.82 1.48p-value {0.0781} {0.4312} p-value {0.0932} {0.2237}

G. IROA x LTV Quadrants H. IPM x LTV Quadrants

LTV LTVlow high chi-squared low high chi-squared

high 10.4% 11.9% 0.30 high 9.4% 13.7% 1.44 IROA (38/367) (21/176) {0.5830} IPM (31/330) (29/213) {0.2304}

low 13.1% 17.4% 1.74 low 14.1% 17.6% 1.18(23/176) (64/367) {0.1873} (30/213) (58/330) {0.2776}

chi-square 0.86 2.84 chi-square 2.80 2.41p-value {0.3593} {0.0918} p-value {0.0942} {0.1208}