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CEO Inside Debt and Internal Capital Market Efficiency

Abstract

Agency theory argues that managerial equity-based incentives are more effective when firm

solvency is likely while debt-based incentives are more effective when firms face a greater

likelihood of bankruptcy. We examine the relation between chief executive officers’ inside debt

holdings and the internal capital market efficiency of multi-segment firms. We find that CEO

inside debt holdings are associated with conservative capital allocation to firm segments, with the

result driven by financially distressed firms. Further analysis indicates that although CEO inside

debt, on average, is negatively related to firm value, the relation is positive for financially

distressed firms. Our evidence indicates that inside debt holdings align the interests of managers

and external creditors, inducing managers to pursue conservative capital allocation strategies that

appear to be optimal for firms facing insolvency.

JEL classifications: G30, G31, G32

Keywords: CEO Inside Debt; Investments; Capital Allocation; Internal Capital Market Efficiency;

Firm Value

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1. Introduction

The availability of an internal capital market, free of the constraints imposed by an

imperfect external capital market, is a primary feature that distinguishes conglomerates from

single-segment firms. While the ability to transfer funds across divisions could lead to excess value

for the multi-segment firm, managers' self-interest could just as easily erode this advantage. Datta,

D’Mello, and Iskandar-Datta (2009) find that equity-based compensation, designed to mitigate

manager-shareholder agency conflict, motivates conglomerate chief executive officers (CEOs) to

allocate more resources to divisions with better investment opportunities resulting in greater excess

value. Our paper considers the relation between inside debt, another form of executive

compensation, and internal capital allocation efficiency (allocation efficiency). Edmans and Liu

(2011) argue theoretically that equity-based incentives are more effective when firm solvency is

likely while debt-based incentives are more effective when firms face a greater likelihood of

bankruptcy. We investigate empirically the effects of inside debt on both resource allocation and

excess value of multi-segment firms and how these effects vary with their financial conditions.

Inside debt (pensions and deferred compensation) represents firms’ fixed payment

obligations to the managers upon their retirement and are generally unsecured and unfunded.

Inside debt holders are exposed to the same risk of firm insolvency as other unsecured creditors,

thus inside debt holdings can align the interests of managers and creditors and reduce the agency

cost of debt (Jensen and Meckling, 1976). From the firm perspective, the most important benefit

of inside debt in the CEO compensation package is to reduce the agency cost of debt, which is

ultimately borne by shareholders since debtholders would recognize the risk-shifting tendency of

a CEO compensated strictly by equity (Edmans and Liu, 2011). Recent research on the relations

between inside debt and corporate investment and financing decisions demonstrates that greater

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inside debt leads to conservative corporate policies and firm risk reduction (e.g., Wei and Yermack,

2011; Cassell, Huang, Sanchez, and Stuart 2012; Phan, 2014).

The efficiency of internal capital allocation is rooted in the concept that greater resources

should be allocated to segments with greater opportunities (Rajan, Servaes, and Zingales 2000).

However, segments with greater opportunities could be riskier. Inside debt can nudge CEOs

toward a debtholder-like attitude with regard to firm risk. To the extent that inside debt makes

CEOs risk averse, they would shift funds away from a higher expected return but potentially riskier

segment toward a less risky segment with more stable cash flows.

Capital transfers to segments with potentially lower risk could be beneficial to shareholders

when firms face financial distress that accentuates the risk of bankruptcy and inefficient

liquidation. Although models of firms engaging in risk-shifting (asset substitution) when facing

financial distress abound in theory (e.g. Jensen and Meckling, 1976), there is less empirical support

for its existence.1 On the other hand, there is increasing evidence for risk management (Eckbo and

Thorburn, 2003; Rauh, 2008; Almeida, Campello, and Weisbach, 2011) under similar

circumstances. Consequently, while the presence of equity-based compensation may result in an

increase in allocation efficiency (Datta et al., 2009), particularly if the measure of efficiency is

constructed such that it is increasing in greater allocations toward the more productive but riskier

investment, the presence of inside debt in the CEO's compensation package may exert an opposite

effect on the same measure. We test this hypothesis in this paper.

We begin our analysis by examining the effect of CEO inside debt holdings on internal

capital allocation. Following Wei and Yermack (2011), Cassell et al. (2012), and Phan (2014), we

1 One exception is Eisdorfer (2008).

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construct four measures of CEO inside debt holdings: relative CEO leverage, which is measured

as the ratio of CEO’s debt to equity scaled by the firm’s debt to equity ratio; relative CEO

incentive, which is the marginal change of the CEO’s inside debt over the marginal change of his

inside equity, given a unit change in the overall value of the firm, divided by the marginal change

of firm debt over the marginal change of firm equity given the same unit change in the overall

value of the firm; relative CEO leverage > 1 dummy, which is an indicator variable set to 1 if the

relative CEO leverage is greater than 1, and 0 otherwise; and relative CEO incentive > 1 dummy,

which is an indicator variable set to 1 if the relative CEO incentive is greater than 1, and 0

otherwise.

Using a sample that includes 1,617 firm-year observations of an unbalanced panel of 694

multi-segment firms over the period 2006-2015, we find evidence that CEO inside debt is

associated with conservative capital allocation, which is biased toward segments with lower

investment opportunities but more stable cash flows. We further find that our results are driven by

a subset of firms that are likely experiencing financial distress. Intuitively, financial distress

increases the probability of default on debt payment and subsequent bankruptcy. Shifts in

investment allocations to lower-risk segments, which reduce overall firm risk while improving

cash flow stability, would help firms avoid insolvency and inefficient liquidation.

Having established the relation between CEO inside debt and internal capital allocation,

we examine how CEO inside debt affects the value of multi-segment firms. We note that the

evidence regarding the effect of corporate diversification on firm value is mixed in the literature.

Early research on conglomerates suggests that multi-segment firms typically suffer from a

diversification discount. Berger and Ofek (1995) estimate the effect of diversification on firm

value by comparing the value of the multi-segment firm with the value of a portfolio of pure-play

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firms that match the individual segments.2 They find that diversified firms are valued 13% to 15%

below their stand-alone entities. The diversification discount is often linked to the inefficient

allocation of internal funds across the divisions of a multi-segment firm (e.g., Lamont, 1997; Shin

and Stulz, 1998). However, Campa and Kedia (2002), Graham, Lemmon, and Wolf (2002), and

Villalonga (2004a and 2004b) find that diversification is not necessarily associated with a value

discount.

We do not take a stand on the relation between diversification and firm value but rather

employ the excess-value framework adopted by this line of research to examine the effect of CEO

inside debt on firm value while controlling for variables that are documented to have power to

explain excess value. Our analysis reveals an average negative effect of CEO inside debt on excess

value, which is consistent with the evidence documented by previous research (e.g., Cassell et al.,

2012; Phan, 2014); however, for the subset of firms experiencing financial distress, inside debt is

positively related to excess value. This evidence implies that shareholders recognize the benefits

of CEO inside debt, which motivates conservative capital allocation for firms that are facing

increased probability of debt-payment default and insolvency, precisely when such conservative

policies could reduce the likelihood of bankruptcy.

Our research adds to the stream of literature on the relations between executive

compensation and corporate policies their implications for firm value. First, Edmans and Liu

(2011) demonstrate theoretically that equity-based compensation alleviates managerial agency

problems, resulting in increased firm value in solvent states, whereas inside debt provides

managerial incentives for increasing firm value in insolvent states. Bennett, Guntay, and Unal

2 Berger and Ofek (1995) refer to the difference as the excess value, but since the multi-segment firm is generally

lower in value, the difference is also known as the diversification discount.

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(2015) report that conservative policies, motivated by managerial inside debt holdings, are

beneficial for banks during the financial crisis period. These authors see it as a trade-off of reduced

returns during normal times that pay off with increased protection during a financial crisis period.

Their finding suggests that managerial conservatism motivated by inside debt holdings can be

good for shareholders depending on external market conditions. However, no prior research has

examined the effects of CEO inside debt on the behaviors of firms facing insolvency. Our evidence

that the conservative capital allocation strategy induced by CEO inside debt benefits the

shareholders of financially distressed firms provides first empirical support to Edmans and Liu’s

(2011) theoretical arguments and complements the finding of Bennett et al. (2015).

Second, to the best of our knowledge, our research is the first that provides evidence of the

relation between inside debt and the capital allocation among the segments of a conglomerate. Due

to their diversification, multi-segment firms tend to have lower risk than pure-play firms.

Nevertheless, our finding that CEO inside debt is associated with a conservative internal capital

allocation of multi-segment firm underscores the managerial conservative behavior motivated by

CEO inside debt holdings. We also provide evidence of the relation between inside debt and

conglomerate firm value.

The rest of the paper is organized as follows. Section 2 presents the literature review. We

provide a description of the data, variable construction, and descriptive statistics in Section 3.

Section 4 presents the empirical predictions, models, and results. Section 5 discusses robustness

checks and Section 6 concludes the paper.

2. Literature Review

2.1. Internal Capital Market Efficiency

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There is a long history of finance literature that focuses on internal capital market efficiency

of multi-segment firms. Weston (1970) relates, and summarily dismisses, two criticisms specific

to internal capital markets: the cross-subsidization of unprofitable activities by profitable segments

and the "deep pocket" advantage of conglomerates. During the 1960s and early 1970s, the U.S.

experienced a boom in the number of conglomerates, and the prevailing economic view attributed

the growth to the greater allocation efficiency of internal capital (Lang and Stulz, 1994). Empirical

research on the value of diversification was stimulated following the adoption of Security and

Exchange Commission (SEC) Regulation S-K and Financial Accounting Standards Board (FASB)

Standards No. 14 that required firms to report segment information after December 15, 1977.

Using the newly available data in Compustat, Lang and Stulz (1994) find a negative relation

between the degree of diversification and Tobin's q. Comment and Jarrell (1995) observe lower

stock returns for diversification, and Berger and Ofek (1995) document lower values for

diversified firms compared to the imputed value of the individual segments if they were to exist

as stand-alone entities. Berger and Ofek (1995) further examine the reasons for the reduced value

and find that overinvestment and cross-subsidization are significant factors.

Some dissenting views on the diversification discount include Villalonga (2004a) and

Campa and Kedia (2002), who attribute the discount to self-selection bias in firms’ choice to

diversify, or Graham et al. (2002), who find that additional target segments added by acquisitions

are already trading at a discount prior to becoming part of the conglomerate. Villalonga (2004b)

uses establishment-level data from the U.S. Bureau of Census, instead of the Compustat data, for

analysis and finds a diversification premium.

Scharfstein and Stein (2000) combine rent-seeking division managers with self-interested

headquarters CEOs in a model with two layers of agency issue and obtain a result that weaker

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segments are subsidized by stronger segments. Billet and Mauer (2003) demonstrate that subsidies

to financially constrained segments can increase the value of multi-segment firms. In Rajan et al.

(2000), the CEO misallocates funds to force self-interested division managers to select efficient

investments for a second-best solution to avoid the third-best outcome.

Ozbas and Scharfstein (2009) find evidence to support inefficiencies in the allocation and

conclude that internal capital markets are inefficient with headquarters management agency

problems playing a factor. Datta et al. (2009) argue that if the misallocation is primarily due to the

extraction of private benefits by headquarters CEOs, then equity-based executive compensation

should improve allocation efficiency (Jensen and Meckling, 1976; Agrawal and Mandelker, 1987;

Coles, Daniel, and Naveen 2006). Moreover, if CEOs’ private benefits increase in the

misallocation, then CEO agency conflict will outweigh division managers' rent-seeking as the

primary cause of value destruction. Datta et al. (2009) find support for both hypotheses.

2.2. Inside Debt

In their seminal paper on agency costs of equity and debt, Jensen and Meckling (1976)

introduce the term "inside debt," define it as debt held by the "owner-manager" of the firm, and

suggest that a holding by the manager of the same fraction of the total debt of the firm as his

fraction of the total equity would eliminate the shareholder-debtholder conflict leading to risk-

shifting. The most common forms of inside debt held by managers are pensions and deferred

compensation (Sundaram and Yermack, 2007).

Edmans and Liu (2011) model the optimal level of inside debt by considering not just the

risk-shifting incentive of the manager induced by equity-based compensation, but also managerial

effort, the probability of bankruptcy, and resulting liquidation value. They find that the optimal

inside debt-equity ratio can vary from the firm debt-equity ratio as proposed in Jensen and

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Meckling (1976) and that inside debt is a more effective solution to the agency cost of debt than

either a solvency bonus (John and John, 1993) or dependence on manager's concern for his

reputation (Hirshleifer and Thakor, 1992).3

Since pensions and deferred compensation represent firms’ fixed payment obligations to

the managers upon their retirement and are generally unsecured and unfunded, inside debt holders

are susceptible to the same risk of firm insolvency as other unsecured creditors. Empirical and

anecdotal evidence supports this proposition. Gerakos (2010) examines a sample of 172 firms and

reports that only three of them provide protection to CEO pensions should these firms go bankrupt.

The following piece of anecdotal evidence illustrates the loss of pension benefits incurred by

executives when their firms fell into bankruptcy:

“…More than 100 former General Motors executives who sued the automaker for cutting

their retirement benefits during the company's 2009 bankruptcy had their appeal rejected

today by a federal appeals court… Most top executives’ pensions were cut by two-thirds,

including former CEO Rick Wagoner, whose pension was reduced from $20 million to

about $8.5 million.” (Source: Automotive News, August 7, 2013).4

Empirical research on inside debt lagged behind research on equity-based executive

compensation primarily due to the lack of data. Bebchuk and Jackson (2005) rely on hand-

collected data, and actuarial assumptions and calculations, to estimate the pensions of 51 current

and retired CEOs. They conclude that pensions, as a percentage of total CEO compensation,

constitute a significant component (48.3%), but this measure also exhibits a large variation among

3 For a normative discourse on including inside debt in executive compensation, see Edmans (2012).

4 Available at the following link http://www.autonews.com/article/20130807/OEM02/130809876/retired-gm-execs-

lose-appeal-in-suit-over-pension-cuts. Retrieved on May 11, 2015.

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the executives. Sundaram and Yermack (2007) also find a significant inside debt component in

their larger hand-collected sample, and further conclude that CEO inside debt is positively related

to CEO age and distance to default, an indication that greater inside debt results in more

conservative corporate policies.

A change in the SEC disclosure requirement in late 2006 and the accompanying availability

of more easily accessible data stimulated empirical research related to inside debt. Wei and

Yermack (2011) find that the 2007 filing of proxy statements post SEC disclosure reform on

pension and deferred compensation was accompanied by an increase in bond prices, a decrease in

equity prices, a decrease in volatility of both securities, and decreases in the implied volatility of

exchange-traded options and in the spreads of default swaps associated with the firms. The transfer

in value from equity to debt implies that the revealed inside debt was considered too high on

average, while the lowered volatility and default swap spread indicates that investors expect lower

price volatility induced by the revealed greater inside debt.

Several recent studies argue that inside debt provides a greater alignment of managers’ and

external creditors’ interests, leading to conservative corporate policies and a decrease in firm risk.

Cassell et al. (2012) report that CEO inside debt holdings induce conservative investment and

financing policy choices. Liu, Mauer, and Zhang (2014) find a positive relation between inside

debt and cash holdings, whereas Phan (2014) finds a negative relation between CEO inside debt

and corporate risk-taking in mergers and acquisitions. Bennett et al. (2015) use a sample of bank

holding companies and show that greater inside debt measured in 2006 is associated with lower

default risk and better performance during the subsequent crisis period. As a result, CEO inside

debt leads to lower cost of debt and fewer restrictive debt covenants (Anantharaman, Fang, and

Gong, 2014; Dang and Phan, 2016).

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3. Sample, Variable Construction, and Descriptive Statistics

We form our sample by combining CEO compensation data from Standard & Poor’s (S&P)

Executive Compensation (ExecuComp) database with firm-level accounting data from S&P’s

Compustat (Compustat) and segment-level data from the Compustat Industrial Segment (CIS)

databases. Since a large number of firms do not report inside debt information, we follow Wei and

Yermack (2011) and Cassell et al. (2012) in restricting our sample to multi-segment firms with

positive CEO inside debt holdings to avoid a potential bias in our analysis. The sample spans the

period 2006-2015. We follow previous research (e.g., Berger and Ofek 1995; Datta et al., 2009,

among others) in applying the following filters to the sample: (i) we require firms to have non-

missing segment information on sales, assets, and capital expenditure; (ii) we exclude firms with

$20 million or less in sales; (iii) we exclude firms whose sum of segment sales are not within 1%

of the total firm sales or firms whose sum of segments’ assets are not within 25% of the firm’s

assets; (iv) we exclude firms with segments that have 1-digit SIC code equal to 0 (agriculture), 6

(finance), and 9 (non-operating divisions); (v) we exclude firms that have all segments in the same

industry; (vi) we require at least five industry-matched pure-play firms for each division in the

multi-segment firm based on a 3-digit SIC code match; and (vii) we require data on Compustat to

calculate all other control variables for the multi-segment firms.

Our merged inside debt, accounting, and segment data yield an unbalanced panel of 1,617

firm-year observations of 694 multi-segment firms, whose CEOs have positive inside debt

holdings in the form of pension and deferred compensation over the sample period. We use this

sample to examine the effects of CEO inside debt on internal capital allocation and firm excess

value.

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We follow Rajan et al. (2000) and Datta et al. (2009) in constructing a measure of allocation

efficiency, the industry-adjusted relative value added by allocation (RVIA), as follows:

∑ , (1)

where ωj is the proportion of segment j’s book value of assets to firm assets, qj is segment j’s

Tobin’s q proxied by the asset-weighted average Tobin’s q of all stand-alone firms operating in

the same 3-digit SIC code industry as that of segment j. is the asset-weighted average imputed

qj’s of the multi-divisional firm. Capexj is the capital expenditure of segment j and BAj is the book

value of segment j’s assets whereas / is the asset-weighted average capital expenditure

to assets ratio for matched stand-alone firms operating in the same three-digit SIC industry as

segment j. The variables qj and ωj are measured as of the beginning of the period.

Segment j’s Tobin’s q is proxied by that of industry-matched pure-play firms since market

values are not available for the individual segments. The objective is to measure the segment’s

investment opportunities compared to the other segments of the firm, , as well as the

capital expenditure of the segment normalized by the book value of the segment’s assets compared

to the asset-weighted average equivalent measure for the industry-matched pure-play firms,

.

The weight is the proportion of segment j’s book value of assets to the firm’s book value

of assets. If the investment opportunity is above average for the sector and the investment

allocation is also above average, the weighted product, ,will provide

a positive contribution toward the measure; this will also occur if both the investment opportunity

and the associated allocation are below average. If the investment opportunity and the allocation

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move in opposite directions, the contribution will be negative. By construction, higher positive

RVIA values indicate higher allocation efficiency while lower or negative values of RVIA indicate

sub-optimal allocation efficiency.

Similar to Berger and Ofek (1995) and Datta et al. (2009), we measure firm excess value

as:

, (2)

where MV is the firm’s market value defined as book value of assets plus the difference between

market value and book value of equity, and I(MV) is the imputed value of the multi-segment firm

calculated as the sum of the imputed values of the firm’s n business segments:

∑ ∗ (3)

Salesi is segment i’s sales value and is the median industry multiple of total

capital to sales of stand-alone firms matched to the business segment using the 3-digit SIC code.

We use the following inside debt measures developed by Edmans and Liu (2011) and Wei

and Yermack (2011) to estimate relative CEO leverage and relative CEO incentive:

Relative CEO leverage = (DCEO/ECEO) ÷ (DFIRM/EFIRM), (4)

where DCEO and ECEO is the manager’s inside debt and inside equity, while DFIRM and EFIRM is the

firm debt and equity, including the amount held by the inside manager, and:

Relative CEO incentive = (ΔDCEO/ΔECEO) ÷ (ΔDFIRM/ΔEFIRM). (5)

The relative CEO incentive captures the marginal change of the manager’s inside debt over the

marginal change of his inside equity, given a marginal change of the firm debt over the marginal

change of the firm equity. Two other inside debt measures are the relative CEO leverage > 1

dummy, which is an indicator variable set to 1 if the relative CEO leverage is greater than 1 and 0

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otherwise, and the relative CEO incentive > 1 dummy, which is an indicator variable set to 1 if the

relative CEO incentive is greater than 1 and 0 otherwise.

To account for the effect of equity-based compensation, we calculate and control for CEO

delta, which measures the change in CEO equity, both stock and option holdings, to a one dollar

change in the firm’s stock price, and CEO vega, the change in CEO equity to a 0.01 change in the

firm’s stock return volatility (Core and Guay, 2002).

Previous research (e.g., Rajan et al., 2000) documents that greater diversity decreases

allocation efficiency. Therefore, similar to Datta et al. (2009), we construct three alternative

measures to capture the degree of diversification by multi-segment firms. The inverse Herfindahl

index is the inverse of a firm’s sales-based Herfindahl index, calculated at the beginning of the

year as:

∑∑

, (6)

where j indicates segment j and n is the total number of segments. Our second measure of diversity

is number of segments, which is the number of segments reported by the firm and available in the

CIS data. Our final measure is diversity, developed by Rajan et al. (2000) and defined as:

∑

∑ , (7)

where qj is market-to-book ratio of the segment proxied by the asset-weighted q of stand-alone

firms in the same industry as the firm, ωj is the weight in terms of assets of segment j, n is a number

of the segments of the diversified firm, and ωj and qj are beginning of year values. This measure

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can be interpreted as an asset-weighted coefficient of variation of the individual segment's Tobin's

q ratios.

Table 1 reports the summary statistics for the allocation efficiency measure, RVIA, firms’

excess value, EV, all four CEO inside debt measures, CEO delta, CEO vega, the three diversity

measures, new CEO dummy, CEO age, CEO tenure, favorable tax status dummy, R&D/sales, book

value of assets, the capital expenditures to book value of assets ratio, capex/assets, and Tobin’s q.

Appendix A provides definitions of the variables. The four CEO inside debt measures are similar

in magnitude to those reported by Phan (2014) for the period 2006-2009. A significant number of

CEOs have inside leverage greater than their firm’s leverage, as indicated by the mean of relative

CEO leverage > 1 dummy, 0.47 (0.42 in Phan, 2014). The average book value of the sample firm

is $8.56 billion and the average number of segments is 4.7 ($4.8 billion and 2.84, respectively, in

Datta et al., 2009).5 The allocation efficiency measure, RVIA, and diversification measures are also

similar to those reported by Datta et al. (2009).

4. Empirical Predictions, Models, and Result Discussions

4.1. CEO Inside Debt and Internal Capital Allocation

Inside debt aligns the interests of managers and external creditors, and is expected to

motivate managers to act more conservatively with respect to risk (Jensen and Meckling, 1976;

Edmans and Liu, 2011). Previous empirical research documents that managers’ debt-based

compensation induces risk-decreasing strategies (Sundaram and Yermack, 2007), leading to

5 The difference arises from different sample periods and our screening out firm-year observations that do not have

positive CEO inside debt holdings.

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reduced R&D and financial leverage, increased working capital and firm diversification (Cassell

et al., 2012), increased bond and decreased stock prices, and decreased volatility (Wei and

Yermack, 2011). A shift in capital allocation from a higher expected return but riskier segment to

a less risky one in a multi-segment firm can reduce risk but may also decrease overall firm

performance, implying internal capital allocation inefficiency. Following the foregoing discussion,

we predict a negative relation between CEO inside debt and allocation efficiency.

We first examine the effect of CEO inside debt on allocation efficiency using the following

regression model:

RVIAi,t = α + βCEO Inside Debti,t-1 + θXi,t + γFirm dummies + δYear dummies + εi,t , (8)

where RVIAi,t is a measure of allocation efficiency as defined in Equation 1 for firm i in year t.

CEO inside debt is proxied by either relative CEO leverage or relative CEO incentive. Since these

two variables are heavily skewed to the right, we use their natural logarithm transformation in the

analysis. Xi,t is a vector of control variables.6 We control for firm diversity since Rajan et al. (2000)

demonstrate that an increase in diversity will decrease allocation efficiency. Similar to Datta et al.

(2009), we control for CEO change by using an indicator variable that takes the value of 1 if the

firm has a new CEO, and 0 otherwise. We also control for firm characteristics that include R&D,

firm size, capital expenditures, and Tobin’s q. We use the natural logarithm of the book value of

assets as a proxy for firm size. Datta et al. (2009) report that CEO equity-based compensation is

positively related to allocation efficiency, therefore we additionally include CEO delta and CEO

vega in some specifications. Since inside debt and capital allocation could be related to time-

varying macroeconomic conditions, we control for year-fixed effects. CEO inside debt and capital

6 Similar to previous research, we use contemporaneous variables as controls. However, our results are qualitatively

similar if we lag the control variables by one period.

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allocation could also be related to unobserved time-invariant firm characteristics, such as the

financial conditions of the firms, which raises a concern for potential endogeneity. We alleviate

this endogeneity concern by controlling for firm-fixed effects in the regressions.

Table 2 reports the regression results. Since we have three different proxies for diversity

with qualitatively similar impact on the findings, for brevity we report the results with the inverse

Herfindahl index (results for the other diversity measures are available from the authors upon

request). Columns 1-4 of Table 2 report the results of the RVIA regressions on CEO inside debt

measures, firm characteristics, and firm- and year-fixed effects, but do not include CEO delta and

CEO vega. The coefficients on all proxies of CEO inside debt holdings are negative, ranging from

-0.023 to -0.015, and statistically significant. In Columns 5-8, we further include managerial

equity-based compensation proxied by CEO delta and CEO vega. The coefficients of all measures

of CEO inside debt holdings remain negative, ranging from -0.024 to -0.017, and statistically

significant. The economic effect of CEO inside debt on RVIA is also important. Since the test

variable, relative CEO leverage (relative CEO incentive), is in the natural logarithm form, its

coefficient estimate indicates that, holding other variables unchanged at their sample means, a 1%

increase in relative CEO leverage (relative CEO incentive) is associated with 1.5-1.6 basis points

(1.7 basis points) decrease in RVIA, which is equivalent to approximately 10% of its sample mean

in absolute terms. These results indicate that CEO inside debt is negatively related to allocation

efficiency.

Boards of directors may anticipate the effects of CEO inside debt on internal capital

allocation when they design executive compensation contracts, which implies a possible joint

determination of CEO compensation structure and internal capital allocation. Thus, failing to

control for endogeneity due to a possible joint determination of CEO compensation and internal

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capital allocation may render our coefficient estimates biased and inconsistent. It is ideal if there

were exogenous shocks to CEO inside debt that we could use to identify its effects on internal

capital allocation. However, CEO inside debt compensation is a corporate decision and previous

literature does not provide a clear guidance on any shocks to CEO inside debt that we can use for

our analysis. Therefore, we address this endogeneity concern by running two-stage instrumental

variable (IV) regressions. Following previous research (e.g., Anantharaman et al., 2014; Cassell et

al., 2012; Phan, 2014), we use the natural logarithm of CEO tenure, natural logarithm of CEO age,

and a favorable tax status dummy, all known to be important determinants of inside debt

compensation, as instruments for relative CEO leverage (relative CEO incentive).7 Intuitively, the

older a CEO is and the longer he works for a given firm, the higher are his pension benefits, which

imply positive relations between CEO inside debt holdings and CEO age and tenure. Sundaram

and Yermack (2007) suggest that taxation affects stock option and pension compensation since

these compensation forms enable managers to defer their incomes to future years, which could

lead to net tax savings for both the firm and the executives depending on their marginal tax rates.

We use the presence of a tax-loss carry-forward in a firm’s balance sheet as a proxy for its

favorable tax status. Our selected instruments should be valid because they are directly related to

CEO inside debt measures but there are no obvious reasons to argue that they are directly related

to allocation efficiency other than through CEO inside debt.

7 Since CEO age and CEO tenure are highly correlated, in an unreported test, we alternately drop each from the set of

instruments but our results are qualitatively unchanged. We also consider other instruments, such as liquidity

constraint, state tax rate on individual income, and industry median relative CEO leverage (relative CEO incentive)

suggested by previous studies but these variables do not pass the instrument validity tests in our analysis.

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Table 3 reports the results of the two-stage IV regressions with relative CEO leverage

(Columns 1 and 2) and relative CEO incentive (Columns 3 and 4). The coefficients of the

instruments have the expected signs and are highly significant, indicating that each instrument is

relevant by itself. The F-statistics of the Cragg-Donald weak instrument tests are greater than 10,

suggesting that the selected instruments are not weak. The Hausman endogeneity test validates the

need to correct for endogeneity while the overidentification test indicates that our selected

instruments are valid. Consistent with the results in Table 2, the coefficients on the instrumented

relative CEO leverage and instrumented relative CEO incentive are negative (-0.035 and -0.038

in Columns 2 and 4, respectively) and statistically significant. This evidence indicates that our

results are robust to the correction for endogeneity.

Next, we investigate the relation between CEO inside debt and internal capital allocation

for subgroups of firms characterized by their degrees of financial distress. The agency problem of

debt suggests that firms that face financial distress or a threat of insolvency may engage in risk-

shifting to benefit shareholders (Jensen and Meckling, 1976). The intuition is that as shareholders

of these firms hold residual claims on firm assets, investing in riskier projects may increase the

payoff to the shareholders on the upside but does not affect shareholder value on the downside. In

the worst-case scenario, the payoff to the shareholders is zero when the debt value exceeds the

asset value. In contrast, if these firms follow a risk-management strategy that favors less risky

investment projects, they can safeguard the firm value, which better serves the debtholders’

interest. It is worth noting that there are theoretical arguments (e.g. Almeida et al., 2011) as well

as growing empirical evidence (e.g., Eckbo and Thorburn, 2003; Rauh, 2008) that support risk

management. Following these discussions, we expect the effect of CEO inside debt on

conservative capital allocation to be more pronounced for firms that face financial distress.

21

Similar to previous research (e.g., Denis and Mihov, 2003), we use firms’ Altman’s (1977)

Z-scores to sort firms into financially distressed and undistressed subgroups. The Altman Z-score

is calculated as: Z = 1.2(Working Capital/Total Assets) + 1.4(Retained Earnings/Total Assets) +

3.3(Earnings Before Interest and Taxes/Total Assets) + 0.6(Market Value of Equity/Book Value

of Liabilities) + 0.999(Net Sales/Total Assets). Firms with calculated Altman’s Z scores below

1.81 are considered financially distressed with a high probability of debt payment default and

bankruptcy.

Following this classification, our sample includes 531 firm-year observations with Z-

scores < 1.81 and 1,086 firm-year observations with Z-scores ≥ 1.81. Table 4 reports the results of

the RVIA regressions for the two subgroups. In Columns 1-4, the coefficients of CEO inside debt

measures are all negative, ranging from -0.022 to -0.017, and statistically significant for the

subgroup of financially distressed firms. In contrast, the coefficients of CEO inside debt measures

are statistically insignificant in Columns 5-8 for financially undistressed firms. This evidence is

consistent with our expectation that CEOs of financially distressed firms with larger inside debt

holdings are more likely to follow a conservative capital allocation strategy.

To address endogeneity concern due to a potential joint determination of CEO inside debt

and internal capital allocation, we again turn to the IV regressions using the set of instruments

similar to the one in Table 3. Table 5 reports the second-stage results of the RVIA IV regressions

separately for the financially distressed and undistressed firms. Consistent with the results in Table

4, the coefficients of instrumented relative CEO leverage and instrumented relative CEO incentive

are negative (-0.034 and -0.039, respectively) and statistically significant for the financially

distressed firms but insignificant for the undistressed firms. This result indicates that our finding

is robust to the correction for endogeneity.

22

4.2. Inside Debt and Multi-segment Firm Excess Value

In this section, we investigate the effect of CEO inside debt holdings on the value of multi-

segment firms proxied by their excess values. The results from the previous section indicate that

CEO inside debt has a negative effect on allocation efficiency of multi-segment firms. To the

extent that higher capital allocation to greater investment opportunity but riskier segments creates

more value, we predict a negative relation between CEO inside debt and excess value of the

average multi-segment firm. However, since conservative investment policy may help financially

distressed firms avoid bankruptcy and inefficient liquidation, a capital allocation strategy that is

biased toward the less risky segments would enhance the value of financially distressed firms.

Following this argument, we expect a positive relation between CEO inside debt and the excess

value of financially distressed multi-segment firms.

We examine the effect of CEO inside debt on excess value using the following regression:

EVi,t = α + βCEO Inside Debti,t-1 + θXi,t + Firm fixed effects + Year fixed effects + εi,t, (9)

where EVi,t is a measure of excess value as defined in Equation 2 for firm i in year t and Xi,t is a

vector of control variables including inverse Herfindahl index and firm size. Columns 1-4 of Table

6 reports the results of the firm excess value regressions on CEO inside debt measures, firm

characteristics, and firm- and year-fixed effects, but without controlling for CEO delta and CEO

vega. The coefficients on all proxies of CEO inside debt holdings are negative, ranging from -

0.217 to -0.159, and statistically significant. In Columns 5-8, we further control for managerial

equity-based compensation proxied by CEO delta and CEO vega. The regression results indicate

that all proxies of CEO inside debt holdings are negative, ranging in values from -0.202 to -0.135,

and statistically significant. The economic effect of CEO inside debt on multi-segment firm excess

value is also substantial. The coefficient estimates indicate that, holding other variables unchanged

23

at their sample means, a 1% increase in relative CEO leverage (relative CEO incentive) is

associated with 16-19 basis points (14-17 basis points) decrease in firm excess value. This

evidence suggests that, on average, CEO inside debt is negatively related to multi-segment firm

value. The reduced value could be a direct consequence of the suboptimal capital allocation

induced by CEO inside debt. Moreover, the finding also suggests that as segments with higher

investment opportunities are deprived of funds, they may find it harder to compete with their pure-

play counterparts.

It is possible that a firm’s excess value and CEO inside debt are both correlated with

unobserved firm characteristics, raising the issue of potential endogeneity. To address this concern,

we run IV regressions using the set of instruments similar to the one used in Tables 3 and 5. Table

7 reports results of the two-stage excess value IV regressions with relative CEO leverage

(Columns 1 and 2) and relative CEO incentive (Columns 3 and 4). Consistent with the results in

Table 6, the coefficients of instrumented relative CEO leverage and instrumented relative CEO

incentive are both negative (-0.573 and -0.631, respectively) and statistically significant. This

evidence indicates that our results are robust to the correction for potential endogeneity bias.

In Table 8, we run the excess value regressions separately for financially distressed and

undistressed subgroups. Interestingly, we find that the coefficients of CEO inside debt variables

are positive, ranging from 0.217 to 0.318, and statistically significant for the financially distressed

subgroup. In contrast, the coefficients of CEO inside debt variables are negative, ranging from -

0.245 to -0.147, and statistically significant for the subgroup of financially undistressed firms.

We also run the IV regressions separately for each subgroup of firms sorted on their

financial conditions and report the second-stage results in Table 9. Consistent with the results

reported in Table 8, the coefficients of instrumented relative CEO leverage and instrumented

24

relative CEO incentive are positive (0.284 and 0.342, respectively) and statistically significant for

financially distressed firms. In contrast, the coefficients of the instrumented variables are negative

(-0.322 and -0.368, respectively) and statistically significant for financially undistressed firms.

This evidence indicates that our finding of a positive (negative) relation between CEO inside debt

and excess value of financially distressed (undistressed) multi-segment firms is not sensitive to the

correction for endogeneity.

To the extent that CEO inside debt motivates corporate risk-decreasing behavior, it may

reduce the bankruptcy risk of financially distressed firms. In this context, investors may view the

conservative capital allocation policy pursued by financially distressed firms as optimal and, thus

be willing to assign a higher value to these firms. Conversely, we do not expect investors of

financially undistressed firms to support a conservative capital allocation approach that hampers

corporate growth and adversely affects firm performance. Our finding that CEO inside debt has a

positive (negative) effect on excess value of financially distressed (undistressed) firms is consistent

with this line of argument. Importantly, while the conservative internal capital allocation induced

by CEO inside debt could be value-decreasing for an average firm or firms in solvent states, it

appears to be an optimal investment strategy for financially distressed firms or firms in insolvent

states.

5. Robustness Checks

We run several additional tests to verify the robustness our results and summarize our

findings in this section. Our measure of allocation efficiency, which follows Rajan et al. (2000)

and Datta et al. (2009), is increasing in value when a firm's segments with relatively greater

investment opportunity obtain a relatively greater share of firm resources. In the first robustness

25

check, we validate our conjecture that segments with greater opportunity are also more risky. Since

investment opportunity is proxied by Tobin's q, which is not available for individual segments for

a multi-segment firm, we use a sample of single-segment firms for analysis. Table A1 in the

Internet Appendix presents the results of the regression of firm risk, measured by cash flow

volatility of single-segment firms, on Tobin's q and other control variables.8 Our risk model is

motivated by previous corporate risk-taking studies (e.g., Coles et al., 2006; John, Litov, and

Yeung, 2008). Cash flow volatility is a time series variable calculated as the standard deviation of

seasonally adjusted quarterly EBITDA-to-assets ratios of a single-segment firm over a five-year

period. The control variables include firm size, proxied by the natural logarithm of sales, book

leverage, capital expenditure, and R&D investment, the last two scaled by the book value of assets.

The regression results indicate a positive and significant relation between Tobin's q and single-

segment firms’ cash flow volatility, lending credence to our belief that higher allocations to

segments with lower growth opportunities, which typically yield lower expected returns, may offer

greater cash flow stability in the context of our analysis.

Our argument about a negative relation between CEO inside debt and capital allocation

efficiency of multi-segment firms is grounded on the premise that the capital allocation behavior

induced by CEO inside debt reduces firm risk, which adversely affects the value of financially

undistressed firms but increases value of the financially distressed firms. To validate our argument,

we examine the direct relation between CEO inside debt and the risk of the segment of a multi-

segment firm. To the extent that CEO inside debt motivates risk-decreasing capital allocation

8 Cash flow volatility is the appropriate measure for firm risk in this test since it is a firm-based measure, which is

likely under the control of the CEOs.

26

strategy, we expect a negative relation between CEO inside debt and the segment’s cash flow

volatility, a proxy for segment risk.

Table 10 reports results of the segment-level cash flow volatility on CEO inside debt and

other control variables. Cash flow volatility is calculated as the standard deviation of seasonally

adjusted quarterly EBITDA-to-assets ratios of a segment of a multi-segment firm over a five-year

period. For control variables that are unavailable at the segment level (e.g., market-to-book and

financial leverage), we use firm-level data instead. Due to the missing data of segment-level cash

flow and other variables, the regression sample is small. The estimated results indicate a negative

and significant relation between CEO inside debt measures and segment-level cash flow volatility,

which is consistent with our expectation. To alleviate the problem of missing segment-level cash

flow data of multi-segment firms, in an alternative analysis, we use the average cash flow volatility

of single-segment firms in the same 3-digit SIC industry as a proxy for the risk of a segment of a

multi-segment firm and report the regression results in Table A2 in the Internet Appendix. We find

that our results are qualitatively unchanged. We further examine the relation between CEO inside

debt and segment-level risk for multi-segment firms sorted on the level of financial distress. The

results reported in Table A3 in the Internet Appendix indicate that the negative relation between

CEO inside debt and segment-level risk is only statistically significant for financially distressed

firms.

Intuitively, the risk choice embedded in the internal capital allocation of the multi-segment

firms will ultimately be reflected in the firm risk. Therefore, we examine the relation between CEO

inside debt and firm risk using both the firm-based cash flow volatility and market-based stock

return volatility as alternate surrogates for firm risk. Stock return volatility is calculated as the

standard deviation of daily stock returns of a firm in a given year. The regression results reported

27

in Table 11 indicate that the coefficients of CEO inside debt measures are all negative and highly

significant. This finding suggests that CEO inside debt has a negative effect on multi-segment firm

risks, which is consistent with our expectation.

Next, to ensure that our results are not sensitive to the way we construct the allocation

efficiency variable, we follow Datta et al. (2009) in constructing two additional measures of

allocation efficiency for testing. The first alternative measure is the relative value added by

allocation (RVA) that accounts for both firm and industry adjustments calculated as follows:

∑ ∑ (10)

Whereas the RVIA measure adjusts for industry changes by subtracting out the investment ratio of

the industry-matched stand-alone firms from the investment ratio of the segment, RVA subtracts

out a third component, ∑ , which is the abnormal investment ratio averaged

across all the segments of the firm. The RVA measure avoids treating the total differential funds

available to the conglomerate as a transfer between segments.

The second alternative measure of allocation efficiency is the absolute value added by

allocation (AVA), which is calculated as:

∑ 1 (11)

The only difference between the AVA and RVIA measures lies in the way that the relative

investment opportunities of a segment is captured: the RVIA measure is based on the mean asset-

weighted imputed qj’s of the diversified firm as the benchmark, whereas the corresponding

benchmark for AVA measure is unity.

We substitute RVA and AVA as alternative measures of allocation efficiency for RVIA and

rerun our analysis. Tables A4 and A5 in the Internet Appendix report the results of the allocation

28

efficiency OLS and IV regressions, respectively. The results indicate that our findings persist. In

Tables A6 and A7 in the Internet Appendix, we sort the sample firms into financially distressed

and undistressed subgroups based on the Altman Z-score and rerun the allocation efficiency OLS

and IV regressions for the subgroups. We find that our results continue to hold.

In the final robustness check, we use the Ohlson O-score as an alternative measure of

financial distress. The Ohlson O-score is defined as:

– 1.32 0.407 log 6.03 .

1.43

0.076 .

1.72 1

, 0 2.37

1.83

. (12)

The untabulated results indicate that our findings are qualitatively similar.

6. Summary and Conclusions

We examine the effect of CEO inside debt on the internal capital allocation efficiency and

its implication for the value of multi-segment firms. If agency problems contribute to the

divergence of interests of managers and shareholders, then CEO compensation incentive is

expected to play a role in the allocation efficiency of internal capital markets. Agency theory

predicts that inside debt aligns managers’ interests with those of external creditors and induces

conservative corporate investment and financial policies.

Our evidence demonstrates that CEO inside debt is associated with a conservative capital

allocation strategy, and the relation is driven by firms that are faced with a higher risk of

insolvency. We also find that CEO inside debt holdings, on average, has a negative effect on multi-

29

segment firms’ excess value; however, such relation is positive for firms facing a greater

insolvency risk. We interpret the negative relation between CEO inside debt and firm excess value

as the result of a greater alignment of the interests of managers toward creditors' interests and away

from those of shareholders, which motivates manager's risk-decreasing behavior. On the other

hand, when firms face a serious risk of insolvency, investors appreciate the risk reduction

motivated by managers’ inside debt holdings and consequently assign a larger value to these firms.

Taken together, our empirical evidence supports the agency theoretic argument that managerial

debt-based incentives are more effective when firms face a greater likelihood of bankruptcy.

30

Appendix A: Variable Definitions

Variable Name Construction Data Source Altman Z-score Z = 1.2(Working Capital/Total Assets) + 1.4(Retained

Earnings/Total Assets) + 3.3(Earnings Before Interest and Taxes/Total Assets) + 0.6(Market Value of Equity/Book Value of Liabilities) + 0.999(Net Sales/Total Assets)

Compustat

Book value of assets Total liabilities and shareholder’s equity Compustat Cash flow volatility The standard deviation of seasonally adjusted quarterly

EBITDA-to-assets ratios of a firm over a five-year period Compustat

Capex/assets The capital expenditure of the firm divided by book value of

assets Compustat

CEO age Age of the CEO ExecuComp

CEO delta The change in CEO equity (stock and option holdings) to a one dollar change in the firm’s stock price

Compustat, CRSP and ExecuComp

CEO tenure Number of years that a CEO has held the CEO title at the current firm

ExecuComp

CEO vega The change in CEO equity (stock and option holdings) to a 0.01 change in the firm’s stock returns volatility

Compustat, CRSP and ExecuComp

Diversity The coefficient of variation of the individual segment’s Tobin’s q ratios weighted by the fraction of individual segment’s asset to total firm asset

Compustat

Favorable tax status dummy

An indicator variable that takes a value of 1 if the firm has favorable tax status (i.e., the firm has a loss carryforward), and 0 otherwise

Compustat

Firm excess value (EV)

Logarithm transformation of the ratio of the firm's market value (defined as the book value of assets plus the difference between the market value of equity and the book value of equity) and the sum of the imputed values of the firm's n business segments (See equations 2 and 3 in the text)

Compustat

Firm size Logarithm transformation of the book value of assets Compustat

Industry-adjusted relative value added by allocation (RVIA)

The weighted cross-product of each segment's deviation of imputed Tobin's q (from industry-matched pure-play firms) from the average Tobin's q for the firm and the deviation of each segment's CAPEX/assets from the average CAPEX/assets ratio of industry-matched pure-play firms. The weights are proportions of the segment's book value. (See equation 1 in the text)

Compustat

31

Inside debt The sum of the present value of accumulated pension benefits and deferred compensation

ExecuComp

Inverse Herfindahl index

Inverse of the Herfindahl index based on the sales of the individual segments of the firm

Compustat

New CEO dummy An indicator variable that takes a value of 1 if the firm has a new CEO, and 0 otherwise

ExecuComp

Number of segments Number of discrete segments reported Compustat

R&D/sales Ratio of R&D expenditure divided by total sales Compustat

Relative CEO incentive

The marginal change of the CEO’s inside debt over the marginal change of their inside equity, given a unit change in the overall value of the firm, divided by the marginal change of firm debt over the marginal change of firm equity given the same unit change in the overall value of the firm

Compustat, CRSP and ExecuComp

Relative CEO incentive > 1 dummy

An indicator variable that takes a value of 1 if the relative CEO incentive exceeds 1, and 0 otherwise

Compustat, CRSP and ExecuComp

Relative CEO leverage

The ratio of CEO’s debt-to-equity scaled by the firm’s debt-to-equity ratio

Compustat, CRSP and ExecuComp

Relative CEO leverage > 1 dummy

An indicator variable that takes a value of 1 if the relative CEO leverage exceeds 1, and 0 otherwise

Compustat, CRSP and ExecuComp

Stock return volatility

the standard deviation of daily stock returns of a firm in a given year

CRSP

Tobin’s q Ratio of market value of assets to book value of assets where market value of assets is defined as the market value of equity + preferred stock value + debt in current liabilities + long-term debt − deferred taxes and investment tax credit

Compustat

32

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Table 1: Summary Statistics Table 1 reports the descriptive statistics of the sample that includes 1,617 firm-year observations of an unbalanced panel of 694 unique firms whose CEOs have positive inside debt holdings in the form of pension and deferred compensation over the period 2006–2014. Industry-adjusted relative value added by allocation (RVIA) is the measures of internal capital allocation efficiency. EV is firm excess values. Relative CEO leverage is the ratio of the CEO’s debt-to-equity scaled by the firm’s debt-to-equity ratio. Relative CEO incentive is the marginal change of the CEO’s inside debt over the marginal change of their inside equity, given a unit change in the overall value of the firm, divided by the marginal change of firm debt over the marginal change of firm equity given the same unit change in the overall value of the firm. Relative CEO leverage > 1 dummy is an indicator variable that takes a value of 1 if the relative CEO leverage exceeds 1, and 0 otherwise. Relative CEO incentive > 1 dummy is an indicator variable that takes a value of 1 if the relative CEO incentive exceeds 1, and 0 otherwise. CEO delta is the change in CEO wealth given a one dollar change in the firm’s stock price. CEO vega is the change in CEO wealth given a 0.01 change in the firm’s stock return volatility. Inverse Herfindahl Index is the inverse of the sales-based Herfindahl Index. Number of segments is the total number of segments in the multi-segment firm. Diversity is calculated as the coefficient of variation of segment’s Tobin's q weighted by the fraction of individual segment’s asset to total firm asset. New CEO dummy is an indicator variable that takes a value of 1 if the firm has a new CEO, and 0 otherwise. CEO age is the age of the CEO. CEO tenure is the number of years that a CEO has held the CEO title at the current firm. Favorable tax status dummy is an indicator variable that takes a value of 1 if the firm has favorable tax status (i.e., the firm has a loss carryforward), and 0 otherwise. R&D/sales is a ratio of R&D expenditure to total sales of the firm. Capex/assets is a ratio of capital expenditure to total assets of the firm. Tobin’s q is measured as the market value of assets divided by the book value of assets, where the market value of assets is measured as (the market value of equity + preferred stock value + debt in current liabilities + long-term debt − deferred taxes and investment tax credit).

Variable   N Mean 1st

quartile Median 3rd

quartile Std.

deviation RVIA 1,617 -0.016 -0.007 0 0.003 0.155

EV 1,617 -0.063 -0.394 0.031 0.422 1.17

Relative CEO leverage 1,617 0.767 0.273 0.643 1.126 0.614

Relative CEO incentive 1,617 0.647 0.223 0.509 0.949 0.547

Relative CEO leverage > 1 dummy 1,617 0.47 0 0 1 0.499

Relative CEO incentive > 1 dummy 1,617 0.38 0 0 1 0.485

CEO delta 1,617 5.397 4.484 5.434 6.378 1.397

CEO vega 1,617 3.789 2.546 4.285 5.384 2.081

Inverse Herfindahl index 1,617 2.162 1.319 1.958 2.761 1.045

Number of segments 1,617 4.704 3 4 6 1.701

Diversity 1,617 0.233 0.111 0.19 0.314 0.168

New CEO dummy 1,617 0.15 0 0 0 0.357

CEO age 1,617 56.878 53 57 61 5.83

CEO tenure 1,617 10.108 3 7 13 10.062

Favorable tax status dummy 1,617 0.459 0 0 1 0.498

R&D/sales 1,617 0.011 0 0 0.014 0.024

37

Book value of assets (USD billion) 1,617 8.563 7.569 8.386 9.516 1.4

Capex/assets 1,617 0.059 0.025 0.042 0.074 0.06

Tobin's q 1,617 1.487 1.077 1.32 1.737 0.587

38

Tab

le 2

: C

EO

In

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e D

ebt

and

In

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al C

apit

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lloc

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n E

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Tab

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pre

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res

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of

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all

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effi

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mea

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the

ind

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y-ad

just

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by

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> 1

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tha

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a va

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of 1

if th

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kes

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by th

e fi

rm’s

deb

t-to

-equ

ity

rati

o. R

elat

ive

CE

O in

cent

ive

is th

e m

argi

nal c

hang

e of

the

CE

O’s

insi

de d

ebt o

ver

the

mar

gina

l cha

nge

of th

eir

insi

de e

quit

y, g

iven

a u

nit c

hang

e in

the

over

all v

alue

of

the

firm

, div

ided

by

the

mar

gina

l cha

nge

of f

irm

deb

t ove

r th

e m

argi

nal c

hang

e of

fi

rm e

quit

y gi

ven

the

sam

e un

it c

hang

e in

the

over

all v

alue

of

the

firm

. CE

O d

elta

is th

e ch

ange

in C

EO

wea

lth

give

n a

one

doll

ar c

hang

e in

the

firm

’s s

tock

pri

ce. C

EO

veg

a is

the

chan

ge in

CE

O w

ealt

h gi

ven

a 0.

01 c

hang

e in

the

firm

’s s

tock

ret

urn

vola

tili

ty. N

ew C

EO

dum

my

is a

n in

dica

tor

vari

able

tha

t ta

kes

a va

lue

of 1

if

the

firm

has

a n

ew C

EO

, an

d 0

othe

rwis

e. I

nver

se H

erfi

ndah

l in

dex

is a

pro

xy f

or f

irm

di

vers

ity.

Rem

aini

ng v

aria

bles

are

con

trol

s an

d de

fine

d in

the

App

endi

x. t

-sta

tist

ics

base

d on

het

eros

ceda

stic

ity-

robu

st s

tand

ard

erro

rs

clus

tere

d by

fir

ms

are

repo

rted

in p

aren

thes

es. *

**, *

*, a

nd *

indi

cate

sig

nifi

canc

e at

the

1%, 5

%, a

nd 1

0% le

vels

, res

pect

ivel

y.

Var

iabl

e (1

) (2

) (3

) (4

) (5

) (6

) (7

) (8

) L

agge

d re

lativ

e C

EO

leve

rage

> 1

dum

my

-0.0

23**

-0.0

24**

(2.3

0)

(2

.33)

L

agge

d re

lativ

e C

EO

ince

ntiv

e >

1 d

umm

y -0

.020

**

-0

.021

**

(2

.09)

(2.1

4)

Lag

ged

ln(r

elat

ive

CE

O le

vera

ge)

-0.0

15*

-0

.017

*

(1.6

5)

(1

.69)

L

agge

d ln

(rel

ativ

e C

EO

ince

ntiv

e)

-0.0

16*

-0.0

17*

(1

.71)

(1

.70)

L

agge

d ln

(CE

O d

elta

)

-0.0

05

-0.0

04

-0.0

05

-0.0

04

(1.2

8)

(1.1

1)

(1.3

0)

(1.1

5)

Lag

ged

ln(C

EO

veg

a)

0.

002

0.00

2 0.

002

0.00

2

(0

.85)

(0

.62)

(0

.86)

(0

.59)

N

ew C

EO

dum

my

0.00

7 0.

006

0.00

7 0.

006

0.00

6 0.

005

0.00

6 0.

006

(0

.96)

(0

.87)

(0

.98)

(0

.93)

(0

.89)

(0

.79)

(0

.90)

(0

.85)

In

vers

e H

erfi

ndah

l ind

ex

-0.0

13*

-0.0

13*

-0.0

13*

-0.0

13*

-0.0

14*

-0.0

13*

-0.0

13*

-0.0

13*

(1

.76)

(1

.76)

(1

.72)

(1

.72)

(1

.80)

(1

.79)

(1

.76)

(1

.75)

R

&D

/sal

e -0

.013

-0

.006

-0

.011

-0

.012

-0

.027

-0

.016

-0

.025

-0

.02

(0

.10)

(0

.05)

(0

.09)

(0

.09)

(0

.23)

(0

.13)

(0

.21)

(0

.17)

F

irm

siz

e 0.

005

0.00

5 0.

005

0.00

5 0.

006

0.00

5 0.

006

0.00

5

(1.5

6)

(1.4

4)

(1.4

6)

(1.4

1)

(1.5

2)

(1.4

2)

(1.3

6)

(1.3

2)

Cap

ex/a

sset

s 0.

1 0.

107

0.10

9 0.

112

0.10

7 0.

111

0.11

6 0.

116

(1

.29)

(1

.40)

(1

.43)

(1

.47)

(1

.40)

(1

.46)

(1

.53)

(1

.53)

39

Tob

in’s

q

0.01

0.

009

0.00

9 0.

008

0.01

1 0.

01

0.01

1 0.

01

(0

.99)

(0

.93)

(0

.91)

(0

.87)

(1

.04)

(0

.99)

(0

.96)

(0

.90)

In

terc

ept

-0.1

13**

-0

.111

**

-0.1

13**

-0

.109

**

-0.1

03**

-0

.103

**

-0.1

02**

-0

.101

**

(2

.36)

(2

.33)

(2

.36)

(2

.33)

(2

.08)

(2

.08)

(2

.11)

(2

.10)

Y

ear

fixe

d ef

fect

s Y

es

Yes

Y

es

Yes

Y

es

Yes

Y

es

Yes

F

irm

fix

ed e

ffec

ts

Yes

Y

es

Yes

Y

es

Yes

Y

es

Yes

Y

es

Num

ber

of o

bser

vatio

ns

1,61

7 1,

617

1,61

7 1,

617

1,61

7 1,

617

1,61

7 1,

617

Adj

uste

d R

2 0.

03

0.03

0.

03

0.03

0.

03

0.03

0.

03

0.03

40

Table 3: CEO Inside Debt and Internal Capital Allocation Efficiency – IV Regressions Table 3 presents the results of the two-stage least squares instrumental variable (IV) regressions of internal capital allocation efficiency, measured by the Industry-adjusted relative value added by allocation (RVIA), on CEO inside debt and other control variables. Relative CEO leverage is the ratio of the CEO’s debt-to-equity scaled by the firm’s debt-to-equity ratio. Relative CEO incentive is the marginal change of the CEO’s inside debt over the marginal change of their inside equity, given a unit change in the overall value of the firm, divided by the marginal change of firm debt over the marginal change of firm equity given the same unit change in the overall value of the firm. Remaining variables are controls and defined in the Appendix. t-statistics based on heteroscedasticity-robust standard errors clustered by firms are reported in parentheses. ***, **, and * indicate significance at the 1%, 5%, and 10% levels, respectively.

Variable

First-stage: Second-stage: First-stage: Second-stage:Ln(relative CEO leverage)

RVIA Ln(relative CEO incentive)

RVIA

(1) (2) (3) (4) Ln(relative CEO leverage) -0.035**

(1.98)

Ln(relative CEO incentive) -0.038* (1.86)

Favorable tax status dummy -0.108*** -0.092*** (3.00) (2.90)

Ln(CEO age) 0.746*** 0.751*** (4.20) (4.66)

Lagged ln(CEO delta) -0.153*** -0.004 -0.124*** -0.003 (6.26) (0.72) (5.38) (0.58)

Lagged ln(CEO vega) 0.002 -0.001 -0.038*** -0.003 (0.18) (0.41) (3.46) (0.92)

Ln(CEO tenure) 0.068*** 0.064*** (2.76) (2.92)

Inverse Herfindahl index 0.011 -0.011*** 0.011 -0.011*** (0.68) (2.89) (0.78) (2.88)

New CEO dummy -0.014 0.004 -0.02 0.004 (0.26) (0.36) (0.43) (0.32)

R&D/sale 1.247 -0.05 1.26 -0.051 (1.35) (0.28) (1.58) (0.29)

Firm size 0.094*** 0.006 0.076*** 0.005 (6.02) (1.58) (5.33) (1.48)

Capex/assets -0.567** 0.06 -0.569** 0.058 (2.01) (0.82) (2.36) (0.79)

Tobin’s q 0.237*** 0.015* 0.209*** 0.014 (6.26) (1.69) (6.09) (1.61)

Intercept -2.681*** -0.01 -2.620*** -0.005 (3.75) (0.32) (4.04) (0.17)

Year fixed effects Yes Yes Yes Yes Firm fixed effects Yes Yes Yes Yes Number of observations 1,617 1,617 1,617 1,617

Overidentification test:

χ2 96.25 96.63 p-value 0.17 0.16

Hausman endogeneity test:

χ2 3.55 3.58 p-value 0.06 0.06

41

Cragg-Donald weak identification test: F-statistics 10.69 11.41 Stock-Yogo weak ID test critical values (10% maximum IV size) 11.29 11.29

42

Tab

le 4

: C

EO

In

side

Deb

t, F

inan

cial

Dis

tres

s, a

nd

Inte

rnal

Cap

ital

All

ocat

ion

Eff

icie

ncy

Tab

le 4

pre

sent

s re

gres

sion

res

ults

of

inte

rnal

cap

ital

all

ocat

ion

effi

cien

cy, m

easu

red

by th

e in

dust

ry-a

djus

ted

rela

tive

val

ue a

dded

by

allo

cati

on

(RV

IA),

on

CE

O in

side

deb

t and

oth

er c

ontr

ol v

aria

bles

for

two

subs

ampl

es b

ased

on

the

firm

’s A

ltm

an (

1977

) Z

-sco

re. F

irm

s ar

e ca

tego

rize

d as

fi

nanc

ially

dis

tres

sed

(und

istr

esse

d) if

thei

r Z

-sco

res

are

belo

w (

equa

l or

abov

e) 1

.81.

Rel

ativ

e C

EO

leve

rage

> 1

dum

my

is a

n in

dica

tor

vari

able

th

at t

akes

a v

alue

of

1 if

the

rel

ativ

e C

EO

lev

erag

e ex

ceed

s 1,

and

0 o

ther

wis

e. R

elat

ive

CE

O i

ncen

tive

> 1

dum

my

is a

n in

dica

tor

vari

able

tha

t ta

kes

a va

lue

of 1

if th

e re

lati

ve C

EO

ince

ntiv

e ex

ceed

s 1,

and

0 o

ther

wis

e. R

elat

ive

CE

O le

vera

ge is

the

rati

o of

the

CE

O’s

deb

t-to

-equ

ity

scal

ed

by th

e fi

rm’s

deb

t-to

-equ

ity

ratio

. Rel

ativ

e C

EO

ince

ntiv

e is

the

mar

gina

l cha

nge

of th

e C

EO

’s in

side

deb

t ove

r th

e m

argi

nal c

hang

e of

thei

r in

side

eq

uity

, giv

en a

uni

t cha

nge

in th

e ov

eral

l val

ue o

f th

e fi

rm, d

ivid

ed b

y th

e m

argi

nal c

hang

e of

fir

m d

ebt o

ver

the

mar

gina

l cha

nge

of f

irm

equ

ity

give

n th

e sa

me

unit

cha

nge

in t

he o

vera

ll v

alue

of

the

firm

. Rem

aini

ng v

aria

bles

are

con

trol

s an

d de

fine

d in

the

App

endi

x. t

-sta

tist

ics

base

d on

he

tero

sced

asti

city

-rob

ust

stan

dard

err

ors

clus

tere

d by

fir

ms

are

repo

rted

in

pare

nthe

ses.

***

, **,

and

* i

ndic

ate

sign

ific

ance

at

the

1%, 5

%,

and

10%

leve

ls, r

espe

ctiv

ely.

Fina

ncia

lly D

istr

esse

d F

irm

sF

inan

cial

ly U

ndis

tres

sed

Fir

ms

Var

iabl

e (1

)(2

)(3

)(4

)(5

)(6

)(7

)(8

)L

agge

d re

lativ

e C

EO

leve

rage

> 1

dum

my

-0.0

20**

* -0

.003

(2.7

2)(0

.25)

Lag

ged

rela

tive

CE

O in

cent

ive

> 1

dum

my

-0.0

17**

-0

.015

(2.2

8)

(1.2

3)

Lag

ged

ln(r

elat

ive

CE

O le

vera

ge)

-0.0

22**

*-0

.003

(2

.67)

(0

.50)

L

agge

d ln

(rel

ativ

e C

EO

ince

ntiv

e)

-0.0

21**

-0

.001

(2.4

1)

(0.1

5)L

agge

d ln

(CE

O d

elta

) -0

.007

-0

.006

-0

.009

-0

.008

0.

006

0.00

5 0.

006

0.00

6

(0.8

9)

(0.8

7)

(1.1

3)

(0.9

7)

(0.9

4)

(0.7

5)

(0.8

9)

(0.9

5)

Lag

ged

ln(C

EO

veg

a)

0.00

5*0.

005*

0.00

6*0.

005

0.00

20.

002

0.00

20.

002

(1

.77)

(1

.70)

(1

.87)

(1

.65)

(0

.43)

(0

.44)

(0

.45)

(0

.42)

N

ew C

EO

dum

my

-0.0

06

-0.0

07

-0.0

07

-0.0

08

0.00

5 0.

004

0.00

5 0.

005

(1

.32)

(1

.33)

(1

.47)

(1

.58)

(0

.43)

(0

.34)

(0

.42)

(0

.43)

In

vers

e H

erfi

ndah

l ind

ex

-0.0

08

-0.0

08

-0.0

1 -0

.009

-0

.005

-0

.006

-0

.005

-0

.005

(1.1

6)

(1.1

9)

(1.3

1)

(1.2

7)

(0.5

6)

(0.6

2)

(0.5

6)

(0.5

5)

R&

D/s

ale

-1.6

36**

-1

.596

**

-1.7

45**

-1

.645

**

0.13

6 0.

161

0.13

6 0.

132

(2

.29)

(2

.22)

(2

.32)

(2

.28)

(0

.73)

(0

.89)

(0

.78)

(0

.76)

Fi

rm s

ize

0.00

1 0.

001

0.00

2 0.

002

-0.0

06

-0.0

05

-0.0

06

-0.0

06

(0

.25)

(0

.27)

(0

.43)

(0

.35)

(0

.93)

(0

.79)

(0

.83)

(0

.87)

C

apex

/ass

ets

0.03

9 0.

03

0.04

8 0.

039

0.22

6***

0.

227*

* 0.

228*

**

0.22

7**

43

(0

.53)

(0

.39)

(0

.63)

(0

.52)

(2

.59)

(2

.56)

(2

.58)

(2

.58)

T

obin

’s q

0.

021

0.02

60.

023

0.02

4 0.

004

0.00

50.

004

0.00

4

(1.1

6)

(1.3

7)

(1.2

6)

(1.2

8)

(0.4

3)

(0.5

8)

(0.4

4)

(0.3

8)

Inte

rcep

t -0

.041

-0

.048

-0

.032

-0

.036

-0

.075

* -0

.073

* -0

.075

**

-0.0

76**

(0.9

3)(1

.10)

(0.7

6)(0

.83)

(1

.89)

(1.8

6)(1

.97)

(1.9

9)Y

ear

fixe

d ef

fect

s Y

es

Yes

Y

es

Yes

Y

es

Yes

Y

es

Yes

Fi

rm f

ixed

eff

ects

Y

es

Yes

Y

es

Yes

Y

es

Yes

Y

es

Yes

N

umbe

r of

obs

erva

tions

53

153

153

153

1

1,08

6 1,

086

1,08

6 1,

086

Adj

uste

d R

2 0.

44

0.44

0.

44

0.44

0.

17

0.17

0.

17

0.17

44

Table 5: CEO Inside Debt, Financial Distress, and Internal Capital Allocation Efficiency – IV Regressions Table 5 presents the instrumental variable (IV) two-stage least square regression results of internal capital allocation efficiency, measured by industry-adjusted relative value added by allocation (RVIA), on CEO inside debt and other control variables for two subsamples based on the firm’s Altman (1977) Z-score. Firms are categorized as financially distressed (undistressed) if their Z-scores are below (equal or above) 1.81. Relative CEO leverage is the ratio of the CEO’s debt-to-equity scaled by the firm’s debt-to-equity ratio. Relative CEO incentive is the marginal change of the CEO’s inside debt over the marginal change of their inside equity, given a unit change in the overall value of the firm, divided by the marginal change of firm debt over the marginal change of firm equity given the same unit change in the overall value of the firm. Remaining variables are controls and defined in the Appendix. t-statistics based on heteroscedasticity-robust standard errors clustered by firms are reported in parentheses. ***, **, and * indicate significance at the 1%, 5%, and 10% levels, respectively. Financially Distressed Firms Financially Undistressed Firms Variable (1) (2) (3) (4) Ln(relative CEO leverage) -0.034* 0.01

(1.72) (0.58)

Ln(relative CEO incentive) -0.039* 0.012 (1.68) (0.63)

Lagged ln(CEO delta) -0.011 -0.011 0.003 0.002 (1.34) (1.32) (0.34) (0.32)

Lagged ln(CEO vega) -0.003 -0.005 -0.001 0 (0.87) (1.28) (0.21) (0.08)

Inverse Herfindahl index -0.004 -0.004 -0.016*** -0.016*** (0.67) (0.59) (3.00) (2.99)

New CEO dummy 0 -0.001 0.014 0.014 (0.01) (0.06) (0.90) (0.91)

R&D/sale -0.382 -0.338 -0.152 -0.153 (0.59) (0.53) (0.75) (0.76)

Firm size 0.013** 0.013** 0.003 0.004 (2.20) (2.18) (0.69) (0.71)

Capex/assets 0.093 0.086 0.027 0.028 (0.84) (0.78) (0.29) (0.29)

Tobin’s q 0.037 0.038 0.004 0.004 (1.36) (1.37) (0.42) (0.44)

Intercept -0.089 -0.084 -0.052 -0.054 (1.59) (1.50) (1.31) (1.34)

Year fixed effects Yes Yes Yes Yes Firm fixed effects Yes Yes Yes Yes Number of observations 531 531 1,086 1,086

Overidentification test: χ2 10.08 10.18 117.80 117.78 p-value 0.99 0.99 0.14 0.14

Hausman endogeneity test:

χ2 3.87 3.95 1.36 1.11 p-value 0.05 0.05 0.24 0.29

45

Cragg-Donald weak identification test: F-statistics 12.96 12.08 10.75 10.63

Stock-Yogo weak ID test critical value (10% maximum IV size) 11.29 11.29 9.08 9.08

46

Tab

le 6

: C

EO

In

sid

e D

ebt

and

Fir

m E

xces

s V

alu

e T

able

6 p

rese

nts

regr

essi

on r

esul

ts o

f fi

rm e

xces

s va

lue

(EV

), o

n C

EO

insi

de d

ebt a

nd o

ther

con

trol

var

iabl

es. R

elat

ive

CE

O le

vera

ge is

the

rati

o of

the

CE

O’s

deb

t-to

-equ

ity

scal

ed b

y th

e fi

rm’s

deb

t-to

-equ

ity

rati

o. R

elat

ive

CE

O le

vera

ge >

1 d

umm

y is

an

indi

cato

r va

riab

le th

at

take

s a

valu

e of

1 if

the

rela

tive

CE

O le

vera

ge e

xcee

ds 1

, and

0 o

ther

wis

e. R

elat

ive

CE

O in

cent

ive

> 1

dum

my

is a

n in

dica

tor

vari

able

that

ta

kes

a va

lue

of 1

if

the

rela

tive

CE

O i

ncen

tive

exc

eeds

1, a

nd 0

oth

erw

ise.

Rel

ativ

e C

EO

inc

enti

ve i

s th

e m

argi

nal

chan

ge o

f th

e C

EO

’s

insi

de d

ebt

over

the

mar

gina

l ch

ange

of

thei

r in

side

equ

ity,

giv

en a

uni

t ch

ange

in

the

over

all

valu

e of

the

fir

m,

divi

ded

by t

he m

argi

nal

chan

ge o

f fir

m d

ebt o

ver t

he m

argi

nal c

hang

e of

firm

equ

ity

give

n th

e sa

me

unit

cha

nge

in th

e ov

eral

l val

ue o

f the

firm

. Rem

aini

ng v

aria

bles

ar

e co

ntro

ls a

nd d

efin

ed i

n th

e A

ppen

dix.

t-s

tati

stic

s ba

sed

on h

eter

osce

dast

icit

y-ro

bust

sta

ndar

d er

rors

clu

ster

ed b

y fi

rms

are

repo

rted

in

pare

nthe

ses.

***

, **,

and

* in

dica

te s

igni

fica

nce

at th

e 1%

, 5%

, and

10%

leve

ls, r

espe

ctiv

ely.

V

aria

ble

(1

) (2

) (3

) (4

) (5

) (6

) (7

) (8

) L

agge

d re

lativ

e C

EO

leve

rage

> 1

dum

my

-0.1

65**

-0.1

44**

(2

.54)

(2.1

8)

L

agge

d re

lativ

e C

EO

ince

ntiv

e >

1 d

umm

y

-0.2

17**

*

-0.2

02**

*

(3

.20)

(2.8

8)

Lag

ged

ln(r

elat

ive

CE

O le

vera

ge)

-0.1

59**

*

-0

.135

***

(3

.30)

(2

.69)

L

agge

d ln

(rel

ativ

e C

EO

ince

ntiv

e)

-0.1

88**

*

-0

.168

***

(3

.51)

(2

.93)

L

agge

d ln

(CE

O d

elta

)

0.

127*

**

0.12

8***

0.

122*

**

0.12

5***

(3.9

4)

(4.0

3)

(3.7

6)

(3.9

1)

Lag

ged

ln(C

EO

veg

a)

-0.0

34*

-0.0

40**

-0

.034

**

-0.0

42**

(1.9

3)

(2.2

4)

(1.9

6)

(2.3

5)

Inve

rse

Her

find

ahl i

ndex

-0

.112

***

-0.1

13**

* -0

.112

***

-0.1

12**

* -0

.114

***

-0.1

14**

* -0

.113

***

-0.1

12**

*

(3.8

5)

(3.9

0)

(3.8

4)

(3.8

6)

(3.9

0)

(3.9

1)

(3.8

8)

(3.8

4)

Firm

siz

e 0.

099*

**

0.09

8***

0.

103*

**

0.10

0***

0.

070*

* 0.

071*

**

0.07

5***

0.

074*

**

(3

.79)

(3

.83)

(3

.99)

(3

.89)

(2

.50)

(2

.60)

(2

.70)

(2

.69)

In

terc

ept

-0.6

17**

-0

.601

**

-0.6

11**

-0

.585

**

-0.9

26**

* -0

.912

***

-0.9

08**

* -0

.890

***

(2

.52)

(2

.46)

(2

.50)

(2

.41)

(3

.76)

(3

.69)

(3

.68)

(3

.62)

Y

ear

fixe

d ef

fect

s Y

es

Yes

Y

es

Yes

Y

es

Yes

Y

es

Yes

F

irm

fix

ed e

ffec

ts

Yes

Y

es

Yes

Y

es

Yes

Y

es

Yes

Y

es

Obs

erva

tions

1,

617

1,

617

1,

617

1,

617

1,

617

1,

617

1,

617

1,

617

A

djus

ted

R2

0.11

0.

11

0.11

0.

11

0.11

0.

12

0.11

0.

12

47

Table 7: CEO Inside Debt and Firm Excess Value – IV Regressions Table 7 presents the instrumental variable (IV) two-stage least square regression results of firm excess value (EV), on CEO inside debt and other control variables. Relative CEO leverage is the ratio of the CEO’s debt-to-equity scaled by the firm’s debt-to-equity ratio. Relative CEO incentive is the marginal change of the CEO’s inside debt over the marginal change of their inside equity, given a unit change in the overall value of the firm, divided by the marginal change of firm debt over the marginal change of firm equity given the same unit change in the overall value of the firm. Remaining variables are controls and defined in the Appendix. t-statistics based on heteroscedasticity-robust standard errors clustered by firms are reported in parentheses. ***, **, and * indicate significance at the 1%, 5%, and 10% levels, respectively.

First-stage: Second-stage: First-stage:

Second-stage:

Ln( relative CEO leverage)

EV Ln( relative CEO incentive)

EV

Variable (1) (2) (3) (4) Ln(relative CEO leverage) -0.573*** (4.97)

Ln(relative CEO incentive) -0.631*** (4.84) Favorable tax status dummy -0.101*** -0.083*** (3.00) (2.80)

Ln(CEO age) 0.723*** 0.694*** (4.30) (4.61)

Ln(CEO tenure) 0.061*** 0.060*** (3.11) (3.40)

Lagged ln(CEO delta) -0.109*** 0.021 -0.083*** 0.033 (4.94) (0.55) (3.99) (0.87) Lagged ln(CEO vega) 0.012 -0.022 -0.028*** -0.048** (1.10) (1.11) (2.83) (2.30) Inverse Herfindahl index 0.021 -0.100*** 0.018 -0.100*** (1.34) (3.35) (1.35) (3.37) Firm size 0.037*** 0.070*** 0.022* 0.064*** (2.76) (2.84) (1.86) (2.62) Intercept -2.052*** -0.104 -1.913*** -0.046 (3.08) (0.44) (3.20) (0.19) Year fixed effects Yes Yes Yes Yes Firm fixed effects Yes Yes Yes Yes Number of observations 1,617 1,617 1,617 1,617

Overidentification test:

χ2 41.98 42.98 p-value 0.14 0.11

Hausman endogeneity test: χ2 7.81 6.60 p-value 0.01 0.01

Cragg-Donald weak identification test:

F-statistics 11.90 13.27

48

Stock-Yogo weak ID test critical value (10% maximum IV size) 11.12 11.12

49

Tab

le 8

: C

EO

In

sid

e D

ebt,

Fin

anci

al D

istr

ess,

an

d F

irm

Exc

ess

Val

ue

Tab

le 8

pre

sent

s re

gres

sion

res

ults

of

firm

exc

ess

valu

e (E

V)

on C

EO

insi

de d

ebt a

nd o

ther

con

trol

var

iabl

es f

or tw

o su

bsam

ples

bas

ed o

n th

e fi

rm’s

Alt

man

(19

77)

Z-s

core

. Fir

ms

are

cate

gori

zed

as f

inan

cial

ly d

istr

esse

d (u

ndis

tres

sed)

if th

eir

Z-s

core

s ar

e be

low

(eq

ual o

r ab

ove)

1.

81.

Rel

ativ

e C

EO

lev

erag

e >

1 d

umm

y is

an

indi

cato

r va

riab

le t

hat

take

s a

valu

e of

1 i

f th

e re

lati

ve C

EO

lev

erag

e ex

ceed

s 1,

and

0

othe

rwis

e. R

elat

ive

CE

O in

cent

ive

> 1

dum

my

is a

n in

dica

tor

vari

able

that

take

s a

valu

e of

1 if

the

rela

tive

CE

O in

cent

ive

exce

eds

1, a

nd 0

ot

herw

ise.

Rel

ativ

e C

EO

leve

rage

is th

e ra

tio

of th

e C

EO

’s d

ebt-

to-e

quit

y sc

aled

by

the

firm

’s d

ebt-

to-e

quit

y ra

tio.

Rel

ativ

e C

EO

ince

ntiv

e is

the

mar

gina

l cha

nge

of th

e C

EO

’s in

side

deb

t ove

r th

e m

argi

nal c

hang

e of

thei

r in

side

equ

ity,

giv

en a

uni

t cha

nge

in th

e ov

eral

l val

ue o

f th

e fi

rm, d

ivid

ed b

y th

e m

argi

nal

chan

ge o

f fi

rm d

ebt

over

the

mar

gina

l ch

ange

of

firm

equ

ity

give

n th

e sa

me

unit

cha

nge

in t

he o

vera

ll

valu

e of

the

fir

m.

Rem

aini

ng v

aria

bles

are

con

trol

s an

d de

fine

d in

the

App

endi

x. t

-sta

tist

ics

base

d on

het

eros

ceda

stic

ity-

robu

st s

tand

ard

erro

rs c

lust

ered

by

firm

s ar

e re

port

ed in

par

enth

eses

. ***

, **,

and

* in

dica

te s

igni

fica

nce

at th

e 1%

, 5%

, and

10%

leve

ls, r

espe

ctiv

ely.

V

aria

ble

Fin

anci

ally

Dis

tres

sed

Fir

ms

Fin

anci

ally

Und

istr

esse

d F

irm

s (1

) (2

) (3

) (4

) (5

) (6

) (7

) (8

) L

agge

d re

lativ

e C

EO

leve

rage

> 1

dum

my

0.21

7**

-0.1

74**

(2.1

3)

(2.0

6)

Lag

ged

rela

tive

CE

O in

cent

ive

> 1

dum

my

0.22

8**

-0.2

45**

*

(2.0

8)

(2.7

1)

Lag

ged

ln(r

elat

ive

CE

O le

vera

ge)

0.27

3**

-0.1

47**

(2.3

7)

(2.3

1)

Lag

ged

ln(r

elat

ive

CE

O in

cent

ive)

0.

318*

**

-0.1

99**

*

(2.6

0)

(2.7

3)

Lag

ged

ln(C

EO

del

ta)

0.16

0***

0.

160*

**

0.19

7***

0.

192*

**

0.17

8***

0.

177*

**

0.17

4***

0.

177*

**

(3

.07)

(3

.10)

(3

.24)

(3

.31)

(3

.87)

(3

.86)

(3

.76)

(3

.87)

L

agge

d ln

(CE

O v

ega)

-0

.065

***

-0.0

58**

* -0

.071

***

-0.0

55**

-0

.031

-0

.037

-0

.033

-0

.041

*

(3.0

0)

(2.6

1)

(3.2

9)

(2.4

8)

(1.3

0)

(1.5

7)

(1.4

0)

(1.7

1)

Inve

rse

Her

find

ahl i

ndex

-0

.102

**

-0.0

99**

-0

.096

**

-0.1

02**

-0

.081

**

-0.0

83**

-0

.079

**

-0.0

80**

(2.1

9)

(2.1

4)

(2.1

0)

(2.2

1)

(2.0

4)

(2.1

0)

(2.0

0)

(2.0

2)

Fir

m s

ize

0.03

7 0.

04

0.01

6 0.

019

0.03

0.

038

0.03

8 0.

04

(0

.75)

(0

.81)

(0

.32)

(0

.38)

(0

.68)

(0

.85)

(0

.85)

(0

.89)

In

terc

ept

-0.7

10*

-0.7

44**

-0

.791

**

-0.8

28**

-0

.840

**

-0.8

54**

-0

.849

**

-0.8

33**

(1.9

0)

(1.9

8)

(2.0

8)

(2.1

6)

(2.5

2)

(2.5

3)

(2.5

2)

(2.4

9)

Yea

r fi

xed

effe

cts

Yes

Y

es

Yes

Y

es

Y

es

Yes

Y

es

Yes

F

irm

fix

ed e

ffec

ts

Yes

Y

es

Yes

Y

es

Yes

Y

es

Yes

Y

es

Obs

erva

tions

53

1

531

53

1

531

1,

086

1,

086

1,

086

1,

086

A

djus

ted

R2

0.25

0.

25

0.25

0.

25

0.

09

0.09

0.

09

0.09

50

Table 9: CEO Inside Debt, Financial Distress, and Firm Excess Value – IV Regressions Table 9 presents the instrumental variable (IV) two-stage least square regression results of firm excess value on CEO inside debt and other control variables, for two subsamples based on the firm’s Altman (1977) Z-score. Firms are categorized as financially distressed (undistressed) if their Z-scores are below (equal or above) 1.81. Relative CEO leverage is the ratio of the CEO’s debt-to-equity scaled by the firm’s debt-to-equity ratio. Relative CEO incentive is the marginal change of the CEO’s inside debt over the marginal change of their inside equity, given a unit change in the overall value of the firm, divided by the marginal change of firm debt over the marginal change of firm equity given the same unit change in the overall value of the firm. Remaining variables are controls and defined in the Appendix. t-statistics based on heteroscedasticity-robust standard errors clustered by firms are reported in parentheses. ***, **, and * indicate significance at the 1%, 5%, and 10% levels, respectively.

Variable Financially Distressed Firms Financially Undistressed Firms (1) (2) (3) (4)

Ln(relative CEO leverage) 0.284* -0.322*** (1.75) (2.98)

Ln(relative CEO incentive) 0.342* -0.368*** (1.89) (3.02) Lagged ln(CEO delta) 0.177*** 0.178*** 0.05 0.058 (3.02) (3.09) (0.97) (1.15) Lagged ln(CEO vega) -0.052* -0.038 -0.002 -0.016 (1.87) (1.28) (0.07) (0.61) Inverse Herfindahl index -0.149*** -0.153*** -0.055 -0.057 (3.19) (3.32) (1.48) (1.56) Firm size 0.003 0.004 0.011 0.008 (0.07) (0.09) (0.32) (0.23) Intercept -0.439 -0.492 -0.259 -0.225 (1.31) (1.45) (0.90) (0.78) Year fixed effects Yes Yes Yes Yes Firm fixed effects Yes Yes Yes Yes Number of observations 531 531 1,086 1,086

Overidentification test:

χ2 47.44 47.16 88.05 89.18

p-value 0.17 0.17 0.30 0.28

Hausman endogeneity test: χ2 2.32 3.30 10.69 8.19

p-value 0.13 0.07 0.00 0.00 Cragg-Donald weak identification test:

F-statistics 11.03 10.84 11.55 12.11 Stock-Yogo weak ID test critical value (10% maximum IV size) 11.39 11.39 9.08 9.08

51

Table 10: CEO Inside Debt and Segment-Level Cash Flow Volatility

Table 10 presents the regression results of segment risk, measured by the cash flow volatility of a segment of a multi-segment firm, on CEO inside debt compensation and other controls. Cash flow volatility is calculated as the standard deviation of seasonally adjusted quarterly EBITDA-to-assets ratios of a segment of a firm over a five-year period. Relative CEO leverage is the ratio of the CEO’s debt-to-equity scaled by the firm’s debt-to-equity ratio. Relative CEO incentive is the ratio of the marginal change in the value of CEO inside debt holdings to the marginal change in CEO inside equity holdings given the change in firm value, all scaled by the firm’s respective ratio. CEO delta is the change in CEO equity (stock and option holdings) given a one dollar change in the firm’s stock price. CEO vega is the change in CEO equity (stock and option holdings) given a 0.01 change in the firm’s stock return volatility. Remaining variables are controls and defined in the Appendix. Heteroscedasticity-robust t-statistics clustered by firms are reported in parentheses. ***, **, and * indicate significance at the 1%, 5%, and 10% levels, respectively.

Variable (1) (2) (3) (4)

Lagged ln(relative CEO leverage) -0.102** -0.092**

(2.11) (2.30)

Lagged ln(relative CEO incentive) -0.010** -0.093** (1.96) (2.12)

Lagged ln(CEO delta) -0.028 -0.030

(0.38) (0.40)

Lagged ln(CEO vega) -0.004 -0.075 (0.19) (0.35)

Lagged ln(CEO tenure) 0.013 0.015 0.019 0.022 (0.60) (0.67) (0.57) (0.63)

Lagged ln(CEO cash compensation) 0.083 0.086 -0.003 -0.057 (0.67) (0.68) (0.17) (0.38)

Lagged ln(sales) -0.062** -0.062** -0.061** -0.614** (2.49) (2.50) (2.45) (2.45)

Lagged R&Ds 0.062 0.060 0.063 0.061 (1.19) (1.16) (1.19) (1.17)

Lagged CAPEXs -0.074 -0.073 -0.074 -0.074 (0.95) (0.93) (0.95) (0.94)

Lagged Market-to-book 0.031 0.033 0.043 0.045 (0.71) (0.75) (0.62) (0.64)

Lagged Book leverage -0.035 -0.033 -0.036 -0.033

(1.04) (0.98) (0.89) (0.84)

Intercept 0.075** 0.072** 0.951* 0.970* (2.57) (2.51) (1.87) (1.89)

Firm fixed effects Yes Yes Yes Yes

Number of observations 1,101 1,101 1,101 1,101

Adjusted R2 0.12 0.12 0.12 0.12

52

Tab

le 1

1: C

EO

In

side

Deb

t an

d M

ult

i-S

egm

ent

Fir

m R

isk

Tab

le 1

1 pr

esen

ts th

e re

sult

s of

mul

ti-s

egm

ent f

irm

ris

k m

easu

res

on C

EO

insi

de d

ebt c

ompe

nsat

ion

and

othe

r co

ntro

ls, w

here

fir

m r

isk

is p

roxi

ed

by s

tock

ret

urn

vola

tili

ty o

r ca

sh f

low

vol

atil

ity

in P

anel

s A

and

B, r

espe

ctiv

ely.

Sto

ck r

etur

n vo

lati

lity

is

calc

ulat

ed a

s th

e st

anda

rd d

evia

tion

of

dail

y st

ock

retu

rns

of a

fir

m in

a g

iven

yea

r. C

ash

flow

vol

atil

ity is

cal

cula

ted

as th

e st

anda

rd d

evia

tion

of s

easo

nall

y ad

just

ed q

uart

erly

EB

ITD

A-

to-a

sset

s ra

tios

of a

firm

ove

r a

five

-yea

r pe

riod

. Rel

ativ

e C

EO

leve

rage

is th

e ra

tio

of th

e C

EO

’s d

ebt-

to-e

quit

y sc

aled

by

the

firm

’s d

ebt-

to-e

quit

y ra

tio.

Rel

ativ

e C

EO

inc

enti

ve i

s th

e ra

tio

of t

he m

argi

nal c

hang

e in

the

valu

e of

CE

O in

side

deb

t ho

ldin

gs t

o th

e m

argi

nal c

hang

e in

CE

O i

nsid

e eq

uity

hol

ding

s gi

ven

the

chan

ge in

fir

m v

alue

, all

sca

led

by th

e fi

rm’s

res

pect

ive

rati

o. C

EO

del

ta is

the

chan

ge in

CE

O e

quit

y (s

tock

and

opt

ion

hold

ings

) gi

ven

a on

e do

llar

cha

nge

in t

he f

irm

’s s

tock

pri

ce. C

EO

veg

a is

the

cha

nge

in C

EO

equ

ity

(sto

ck a

nd o

ptio

n ho

ldin

gs)

give

n a

0.01

ch

ange

in th

e fi

rm’s

sto

ck r

etur

n vo

lati

lity

. Rem

aini

ng v

aria

bles

are

con

trol

s an

d de

fine

d in

the

App

endi

x. t-

stat

isti

cs b

ased

on

hete

rosc

edas

ticit

y-ro

bust

sta

ndar

d er

rors

clu

ster

ed b

y fi

rms

are

repo

rted

in

pare

nthe

ses.

***

, **

, an

d *

indi

cate

sig

nifi

canc

e at

the

1%

, 5%

, an

d 10

% l

evel

s,

resp

ecti

vely

. P

anel

A:

Stoc

k R

etur

n V

olat

ilit

y R

egre

ssio

ns

Var

iabl

e (1

) (2

) (3

) (4

) (5

) (6

) (7

) (8

) L

agge

d ln

(rel

ativ

e C

EO

leve

rage

) -0

.276

***

-0.3

82**

* -0

.503

***

-0.5

99**

*

(4.1

9)

(5.3

1)

(7.0

8)

(7.5

3)

Lag

ged

ln(r

elat

ive

CE

O in

cent

ive)

-0

.274

***

-0.4

21**

*

-0.5

55**

*-0

.682

***

(3

.72)

(5

.14)

(6.9

6)

(7.4

1)

Lag

ged

ln(C

EO

del

ta)

-0.2

17**

* -0

.202

***

-0

.232

***

-0.2

11**

*

(3.2

3)(3

.07)

(3

.21)

(2.9

7)L

agge

d ln

(CE

O v

ega)

0.

008

-0.0

14

0.

042*

0.

008

(0

.39)

(0

.63)

(1.7

6)

(0.3

3)

Lag

ged

ln(C

EO

tenu

re)

-0.0

81**

-0.0

82**

-0.0

14-0

.014

-0.0

11-0

.01

0.05

90.

064

(2

.10)

(2

.11)

(0

.33)

(0

.33)

(0

.26)

(0

.23)

(1

.28)

(1

.38)

L

agge

d ln

(CE

O c

ash

com

pens

atio

n)

-0.0

35

-0.0

38

-0.0

46

-0.0

52

0.01

0.

007

0.00

8 0.

001

(0

.86)

(0.9

3)(1

.10)

(1.2

6)(0

.20)

(0.1

4)(0

.16)

(0.0

1)L

agge

d ln

(sal

es)

-0.2

33**

* -0

.241

***

-0.1

41**

* -0

.144

***

-0.2

02**

* -0

.216

***

-0.1

24**

* -0

.127

***

(7

.88)

(8

.12)

(3

.52)

(3

.59)

(6

.16)

(6

.63)

(3

.21)

(3

.32)

L

agge

d m

arke

t-to

-boo

k -0

.399

***

-0.4

08**

*-0

.255

***

-0.2

60**

*-0

.195

**-0

.208

**-0

.051

-0.0

57

(4.3

6)

(4.4

4)

(3.1

3)

(3.1

8)

(2.2

1)

(2.3

5)

(0.5

6)

(0.6

4)

Lag

ged

R&

D

2.06

7 1.

783

1.67

1.

605

10.5

91**

* 10

.499

***

10.2

86**

* 10

.577

***

(0

.85)

(0.7

3)(0

.71)

(0.6

8)(3

.90)

(3.8

6)(3

.92)

(4.0

3)L

agge

d C

APE

X

2.67

6**

2.75

3**

2.67

5*

2.70

4**

-0.1

15

-0.1

08

-0.0

26

-0.1

28

(1

.98)

(2

.03)

(1

.96)

(1

.97)

(0

.08)

(0

.08)

(0

.02)

(0

.09)

L

agge

d B

ook

leve

rage

0.

727*

0.77

8**

0.51

80.

536

-0.9

47**

-0.9

55**

-1.0

89**

-1.1

19**

53

(1

.87)

(1

.99)

(1

.38)

(1

.41)

(2

.13)

(2

.12)

(2

.48)

(2

.51)

In

terc

ept

4.39

0***

4.43

7***

6.31

4***

6.31

0***

4.55

3***

4.67

6***

4.71

1***

4.79

3***

(1

1.46

) (1

1.53

) (1

4.05

) (1

4.06

) (1

0.35

) (1

0.54

) (1

0.58

) (1

0.70

) Fi

rm f

ixed

eff

ects

N

o N

o N

o N

o Y

es

Yes

Y

es

Yes

In

dust

ry f

ixed

eff

ects

Y

esY

esY

esY

esN

oN

oN

oN

oN

umbe

r of

obs

erva

tions

1,

123

1,12

3 1,

123

1,12

3 1,

123

1,12

3 1,

123

1,12

3 A

djus

ted

R2

0.25

0.

24

0.26

0.

26

0.22

0.

22

0.23

0.

23

Pan

el B

: C

ash

Flo

w V

olat

ilit

y R

egre

ssio

ns

Var

iabl

e

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

Lag

ged

ln(r

elat

ive

CE

O le

vera

ge)

-0.1

86**

* -0

.194

***

-0.2

04**

* -0

.205

***

(3

.27)

(3.1

5)(4

.08)

(3.9

5)L

agge

d ln

(rel

ativ

e C

EO

ince

ntiv

e)

-0.1

65**

* -0

.300

***

-0.1

85**

* -0

.207

***

(2

.69)

(4

.24)

(3

.31)

(3

.28)

L

agge

d ln

(CE

O d

elta

) 0.

026

0.01

80.

024

0.03

6

(0.5

1)

(0.3

4)

(0.4

4)

(0.6

7)

Lag

ged

ln(C

EO

veg

a)

-0.0

49

-0.0

49

-0.0

35

-0.0

46

(1

.64)

(1.5

7)(1

.13)

(1.4

7)L

agge

d ln

(CE

O te

nure

) -0

.01

-0.0

12

-0.0

1 0.

022

-0.0

19

-0.0

2 -0

.017

-0

.018

(0.3

2)

(0.3

7)

(0.3

1)

(0.5

9)

(0.6

0)

(0.6

3)

(0.4

4)

(0.4

7)

Lag

ged

ln(C

EO

cas

h co

mpe

nsat

ion)

-0

.015

-0.0

17-0

.023

-0.0

150.

017

0.01

60.

013

0.01

1

(0.4

6)

(0.5

2)

(0.6

7)

(0.4

4)

(0.5

1)

(0.4

8)

(0.3

9)

(0.3

3)

Lag

ged

ln(s

ales

) -0

.134

***

-0.1

39**

* -0

.113

***

-0.1

16**

* -0

.104

***

-0.1

10**

* -0

.091

**

-0.0

95**

(5.0

3)(5

.29)

(3.1

8)(3

.12)

(3.5

1)(3

.75)

(2.2

6)(2

.33)

Lag

ged

mar

ket-

to-b

ook

0.00

3 -0

.005

0.

018

0.04

8 0.

024

0.01

5 0.

031

0.02

3

(0.0

6)

(0.0

9)

(0.2

8)

(0.7

7)

(0.4

0)

(0.2

5)

(0.5

0)

(0.3

7)

Lag

ged

R&

D

-2.2

5-2

.51

-1.8

08-1

.865

2.79

22.

743.

193

3.27

2

(0.7

6)

(0.8

4)

(0.6

0)

(0.6

1)

(1.1

2)

(1.0

9)

(1.2

7)

(1.2

9)

Lag

ged

CA

PEX

5.

626*

**

5.69

5***

5.

526*

**

6.77

0***

0.

19

0.17

0.

068

0.02

2

(4.7

2)(4

.73)

(4.6

3)(5

.89)

(0.1

8)(0

.16)

(0.0

7)(0

.02)

Lag

ged

Boo

k le

vera

ge

0.11

7 0.

182

0.12

-0

.436

-0

.729

**

-0.6

90**

-0

.730

**

-0.7

11**

(0.3

7)

(0.5

7)

(0.3

6)

(1.4

6)

(2.5

2)

(2.3

8)

(2.4

6)

(2.3

6)

Inte

rcep

t 5.

797*

**5.

839*

**5.

492*

**1.

678*

**

2.02

0***

2.04

3***

1.94

0***

1.95

1***

(2

2.48

) (2

2.46

) (1

4.52

) (5

.40)

(6

.97)

(7

.03)

(6

.24)

(6

.32)

F

irm

fix

ed e

ffec

ts

No

No

No

No

Yes

Y

es

Yes

Y

es

Indu

stry

fix

ed e

ffec

ts

Yes

Yes

Yes

Yes

No

No

No

No

Num

ber

of o

bser

vatio

ns

1,12

4

1,12

4

1,12

4

1,12

4

1,12

4

1,12

4

1,12

4

1,12

4

Adj

uste

d R

2 0.

247

0.24

4 0.

251

0.20

7 0.

239

0.23

6 0.

240

0.23

8