1

A Test of the Free Cash Flow Hypothesis: The Impact of Increased

Institutional Holdings on Firm Characteristics*

SIGITAS KARPAVICIUS† and FAN YU

‡

July 19, 2011

ABSTRACT

This paper tests the free cash flow hypothesis and analyzes the impact of the increased

institutional ownership on firm characteristics. Institutional ownership of U.S. equities increases

from 7.3% in 1980 to 45.7% in 2009. Greater institutional ownership reduces the agency

problem of free cash flow. We find that the increased institutional ownership results in the lower

leverage and payout that consequently lead to greater cash holdings and firm value. The results

support the free cash flow hypothesis and provide an alternative explanation why firms hold so

much cash and why debt and payout ratios decrease during the last 30 years.

Key words: Agency problem; Free cash flow hypothesis; Institutional ownership; Cash holdings;

Capital structure; Payout policy

JEL classification: G23; G32; G35

* We thank Jarrad Harford and seminar participants at the Shanghai University of Finance and Economics and 2011

China International Conference in Finance for their helpful comments and suggestions. † Corresponding author. Address: Flinders Business School, Flinders University, GPO Box 2100, Adelaide SA 5001,

Australia. E-mail: sigitas.karpavicius@flinders.edu.au. ‡ Foster School of Business, Box 353200, University of Washington, Seattle, WA 98195, USA.

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The average cash-to-assets ratio for U.S. industrial firms doubles from 1980 to 2009. Classical

agency theory predicts that corporate managers with substantial free cash flow are more likely to

invest in negative net present value (NPV) projects even if paying out cash is better for

shareholders (Jensen (1986), Stulz (1990)). Jensen (1986) suggests using debt and cash payout to

control the agency problem associated with excess cash flow accessible to managers. These two

mechanisms help prevent such firms from wasting resources on low-return projects. The passive

monitoring has its costs: cash constraint and cost of raising external capital (Jensen and Meckling

(1976), Myers and Majluf (1984)), overleverage (Campello (2006)), agency costs associated with

debt (Myers and Majluf (1984)), and underinvestment (Myers (1977)).

Meanwhile, the average institutional ownership of U.S. industrial firms increases almost seven

times (from 7.3% in 1980 to 45.7% in 2009). Prior literature suggests that the presence of

institutional investors is associated with lower information asymmetry, better corporate

governance, and lower agency costs (see Hartzell and Starks (2003), Szewczyk, Tsetsekos, and

Varma (1992), Brous and Kini (1994), Velury and Jenkins (2006), O’Neill and Swisher (2003)).

The dramatic change in ownership structure gives us an excellent opportunity to analyze its

impact on controlling the agency problem associated with excess cash flow. The goal of this

paper is to test the free cash flow hypothesis and investigate the impact of increased institutional

holdings in corporate equities on cash balances and on two mechanisms that reduce agency costs

of excess cash flow – leverage and payout (the sum of dividends and share repurchase).

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The empirical evidence on free cash flow hypothesis is mixed. Lang, Stulz, and Walkling (1991)

find support for free cash flow hypothesis by analyzing a sample of U.S. successful tender offers

from 1980 to 1986. They report that bidder returns are significantly negatively related to cash

flow for bidders with low Tobin’s q but not for high Tobin’s q bidders. However, Gregory

(2005) uses UK takeovers of listed domestic companies during the period 1984 to 1992 and finds

no support for free cash flow hypothesis. Griffin (1988) analyses the petroleum industry during

the period 1979 to 1985 and finds support for the hybrid free cash flow model. Lehn and Poulsen

(1991) analyze the source of stockholder gains in going private transactions. The authors find

that the major source of the gains is the mitigation of agency problems associated with free cash

flow. Lang and Litzenberger (1989) analyze dividend announcements and provide the support

for the free cash flow hypothesis. In contrast, Howe, He, and Kao (1992) analyze tender offer

share repurchase and specially designated dividend announcements and find no support for free

cash flow theory. Richardson (2006) finds evidence that over-investment is concentrated in firms

with the highest levels of free cash flow supporting free cash flow hypothesis.

A relatively small sample size is the common drawback of most of these studies. For example,

Lang, Stulz, and Walkling (1991) have totally 101 observations in their sample; Griffin (1988)

uses the panel data set for 25 firms; the sample size of Lehn and Poulsen (1989) is 236

observations; the sample in Gregory (2005) consists of 217 observations. Bathala, Moon, and

Rao (1994) test their hypotheses using 516 observations. However, the sample of Richardson

(2006) covers 58,053 firm-year observations. Our paper uses a much larger sample that consists

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of more than 140,000 observations. It spans over three decades and covers most of Compustat

firms.

Another stream of literature focuses on the increasing cash balances of industrial firms. Recent

literature documents that the increased cash holdings are in line with the rational behavior of a

firm. Opler et al. (1999) find that firms with better growth prospects and riskier cash flow tend to

hold more cash. Bates, Kahle, and Stulz (2009) point out that the cash increase is due to the

changes in firm characteristics. They find that the increasing risk in cash flow and the greater

importance of research and development (R&D) expense relative to capital expenditure

(CAPEX) requires firms to hold more cash. The literature suggests that if a firm cannot take a

full advantage of the growth opportunities, it risks being predated and losing its market share.

For example, Chevalier (1995) investigates supermarket leveraged buyouts (LBOs). She finds

that the prices decrease in the local market following an LBO if the rival firms are not highly

leveraged while the prices rise if rival firms are also highly leveraged. Haushalter, Klasa, and

Maxwell (2007) report that firms hold more cash and use more derivatives if they share a larger

proportion of their growth opportunities with rivals.

Further, Faulkender and Wang (2006) find that additional cash is most highly valued by

shareholders of firms with low levels of cash holdings; however, the value of additional cash

diminishes in the level of cash holdings. Foley et al. (2007) argue that the tax costs associated

with repatriations contribute to the magnitude of cash holdings. Harford, Mansi, and Maxwell

(2008) find that cash holdings increase with stronger corporate governance.

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We argue that concentrated institutional ownership, measured as the ownership controlled by

five largest institutional investors, is an alternative monitoring mechanism for agency problem.

The results show that institutional monitoring has partially substituted debt and payout as the

increase in institutional holdings leads to the lower debt and payout ratios. As institutions are

good monitors, the decreased debt and payout result in greater cash balances rather than to

investments in negative NPV projects. Further, cash reserves are positively affected by greater

institutional holdings. In the analysis, we control for the predation risk and still find that the cash

holdings are higher for firms with greater institutional ownership. At last, we show that greater

cash balances enhance firm value. It is consistent with shareholder wealth maximization. The

results are statistically and economically significant and robust for both high-tech and non high-

tech firms. This study provides empirical support for free cash flow hypothesis and helps explain

the evolution of leverage, cash balances, and payout ratio during the last 30 years.

The rest of the paper is structured as follows. Section I develops testable hypotheses. Section II

describes the sample. Obtained results are detailed in Section III. Finally, Section IV concludes.

I. Hypotheses Development

We start from the free cash flow hypothesis. It assumes that managers want to invest all the

available funds even in negative NPV projects. This conflict is not likely to be resolved by

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contracts based on cash flow and investment expenditure. The use of debt can decrease the free

cash flow available to managers through repayment to debtholders (Jensen and Meckling (1976),

Jensen (1986)). Jensen (1986) suggests also using dividends. Similarly, by paying to

shareholders, a firm’s free cash flow decrease. Managers are less likely to invest in value

destroying projects if they do not have sufficient funds. Alternative mechanism for controlling

inefficient investment is through monitoring. We use ownership controlled by five largest

institutional investors (Top5 holdings) as a proxy for monitoring.1

Empirical studies suggest that institutions are good monitors. Carleton, Nelson, and Weisbach

(1998) use a private database consisting of the correspondence between TIAA-CREF and 45

firms it contacted about governance issues between 1992 and 1996, to analyze the process of

private negotiation between financial institutions and the companies they attempt to influence.2

They find that at least 87% of the firms took actions. A survey conducted by McCahery, Starks,

and Sautner (2010) found that the majority institutions that responded to their survey are willing

to engage in shareholder activism. Chen, Harford, and Li (2007) use acquisition decisions to

reveal monitoring and find that firms with concentrated holdings of independent long-term

institutions are more likely to make withdrawal of bad bids. Hartzell and Starks (2003) find that

1 As a robustness check, we use total institutional holdings as the proxy for monitoring and our results are even

stronger. 2 TIAA-CREF is the abbreviation of Teachers Insurance and Annuity Association - College Retirement Equities

Fund.

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firms with higher concentrated institutional holdings are associated with lower level of CEO

compensation and higher pay-for-performance sensitivities.3

If monitoring by concentrated institutional investors can substitute higher leverage and higher

payout ratio as controlling mechanism, then firms with higher Top5 holdings will have lower

leverage and lower payout ratio. This leads to our first two hypotheses:

Hypothesis 1: Higher ownership controlled by five largest institutional investors will be

associated with lower leverage.

Hypothesis 2: Higher ownership controlled by five largest institutional investors will be

associated with lower payout ratio.

The debt and payout policies are insufficient to discourage the managers not to engage into low-

return projects. It is likely that firms still invest in negative NPV projects, but less than in

absence of debt and payout. The monitoring and pressure by the institutional investors might

discourage firm management to invest in negative NPV projects. Thus, we expect a positive

relationship between institutional ownership and cash holdings:

Hypothesis 3: Higher ownership controlled by five largest institutional investors will be

associated with higher cash holdings.

In presence of good monitoring, lower debt and payout ratios mechanically lead to greater cash

3 However, prior studies also show that institutional investors do not always have influence on a firm’s corporate

governance. Karpoff, Malatesta, and Walkling (1996) find no persuasive evidence that shareholder proposals

increase firm value. However, it might be due to the actions behind the door before the initiation of shareholder

proposal.

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balances rather than to investment in negative NPV projects. Our next two hypotheses are as

follows:

Hypothesis 4: There will be a negative relationship between cash holdings and leverage.

Hypothesis 5: There will be a negative relationship between cash holdings and payout

ratio.

It is costly to use debt and payout to reduce agency costs of free cash flow. Both mechanisms

reduce firm’s financial flexibility. A firm must forego some good projects if they require quick

response or the external financing is too costly for the firm (Myers and Majluf (1984)). Firm

value is hurt by insufficient internal funds. Besides, if a firm shares a large portion of investment

opportunities with its rivals, it risks being predated and losing market share if it cannot make

sufficient investment. Haushalter, Klasa, and Maxwell (2007) find inter- and intra-industry

evidence that the extent of the interdependence of a firm’s investment opportunities with rivals is

positively associated with its use of derivatives and the size of its cash holdings. Campello

(2006) shows that debt taking can both boost and hurt firm performance: moderate debt taking is

associated with relative-to-rival sales gains; and high indebtedness leads to product market

underperformance. Further, Dittmar and Mahrt-Smith (2007) show that good corporate

governance improves the value of cash reserves and so enhances firm value. We would expect

that a firm which adopts better monitoring is more likely to enhance its value by increasing its

cash holdings:

Hypothesis 6: Cash holdings will be positively associated with firm value.

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Figure 1 illustrates our hypotheses.

[Insert Figure 1 here]

II. Data

Our initial sample is drawn from Compustat. It covers the period 1980 through 2009. We

eliminate financial firms (with Standard Industrial Classification (SIC) codes 6000-6999) since

they have different capital structure and their cash balances might be subject to the regulatory

authority. We also exclude public utility firms (with SIC codes 4900-4999) because they operate

in regulated industries and their financing and capital structure decisions might be impacted by

the changes in the regulatory environment. To be included in the sample, firms must have

positive book value of assets (Compustat item AT), positive sales (Compustat item SALE),

positive common shares outstanding (Compustat item CSHO), positive closing share price at the

end of the fiscal year (Compustat item PRCC_F), and be incorporated in the United States.

Fama and French (2001) report that the population of firms has changed over time. The

proportion of small firms with low profitability but high growth opportunities has increased. It is

likely that these firms are from high-tech sector. Thus, we control for industry (high-tech vs. non

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high-tech) in the analysis by including high-tech dummy in the models. Consistent with

TechAmerica, we use 45 SIC codes to define the high-tech industry.4

Table I presents the number of all firms, high-tech firms, and non high-tech firms in each year.

The last column reports the high-tech firms ratio (the number of high-tech firms over the number

of all firms in each year). We find that the ratio of high tech firms increases from 14.7% to

24.9% during the sample period.

[Insert Table I here]

Table I presents the evolution of institutional ownership during the sample period. Institutional

ownership is the percentage of shares held by institutional investors. We assume that firms not

covered by Thomson Reuters have no institutional investors. We winsorize institutional

ownership at one to avoid non-meaningful numbers. The mean (median) institutional ownership

increases from 7.3% (0.0%) in 1980 to 45.7% (47.9%) in 2009. In addition, we report the

institutional ownership for high-tech and non high-tech firms. We find that the institutional

ownership is quite similar for both sectors over the whole sample period. We also find that the

mean (median) value of Top5 holdings increases from 4.8% (0.0%) to 21.4% (23.0%) from 1980

4 TechAmerica is a U.S. technology trade association. It was formed from the merger of AeA (formerly known as the

America Electronics Association), the Cyber Security Industry Alliance (CSIA), the Government Electronics &

Information Technology Association (GEIA), and the Information Technology Association of America (ITAA) in

2009. 45 SIC codes can be retrieved from http://www.techamerica.org/sic-definition.

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to 2009. The substantial changes in the ownership structure over the three decades should have

impacted firms’ financing and capital structure decisions.

The increase in institutional holdings can be explained by the general increase in the financial

assets of institutional investors over the sample period. Financial assets of institutional investors

in the U.S.A. increase from $11.2 trillion in 1995 to $24.2 trillion in 2007 (in constant 2000 U.S.

dollars). This corresponds to 140.8% and 211.2% of GDP respectively (Gonnard, Kim, and

Ynesta (2008)). Thus, we can assume that the increase in institutional ownership is exogenous.

Nevertheless, for robustness, we still control for the possible endogeneity.

Table II presents the evolution of cash balances over time. We use two measures of cash

balances: book cash ratio (cash and short-term investments (Compustat item CHE) over book

value of assets) and market cash ratio (cash and short-term investments over market value of

assets).5 To mitigate the impact of outliers and errors, we winsorize the values of both cash ratios

at the tails of 0.5% and 99.5%. We find the substantial increase in cash holdings over time as

illustrated in Table II. Market (book) cash ratio increases from 7.6% to 13.2% (from 10.6% to

22.6%) over the sample period. The median values are smaller but have similar dynamics. We

also divide our sample into non high-tech firms and high-tech firms. The evolution of cash

balances for both subsamples is similar.

[Insert Table II here]

5 Market value of assets = book value of assets – common equity (Compustat item CEQ) + common shares

outstanding * closing share price at the end of the fiscal year.

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Table III presents the dynamic of leverage over the sample period. We measure leverage using

book leverage (debt over book value of assets) and market leverage (debt over market value of

assets).6 We winsorize the values of both debt ratios at the tails of 0.5% and 99.5%. We find that

the mean (median) market leverage decreases from 23.1% to 15.9% (from 19.8% to 9.4%)

during the 1980-2009 period. However, the evolutions of mean and median book leverage are

quite different: mean book leverage slightly increases (from 26.9% to 28.7%) whereas median

book leverage decreases from 24.5% to 15.7%. Consistent with the prior empirical studies, we

find that high-tech firms tend to have lower debt ratios than non high-tech firms.

[Insert Table III here]

Next, we compute the payout ratio. It is a sum of common stock dividends (Compustat item

DVC) and absolute value of the difference between purchase of common and preferred stock

(Compustat item PRSTKC) and preferred stock redemption value (Compustat item PSTKRV)

divided by market value of equity (common shares outstanding * closing share price at the end of

the fiscal year). We find that this variable has a lot of outliers; thus, we winsorize it at the tails of

5% and 95%. The evolution of the payout ratio over the sample period is shown in Table IV. The

mean (median) payout ratio decreases from 5.5% to 3.1% (from 2.3% to 0.1%) during the last

6 Debt is the sum of long-term debt (Compustat item DLTT) and debt in current liabilities (Compustat item DLC).

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three decades. We find that the dynamic of payout ratio is impacted by non high-tech industries

as the median payout ratio for high-tech firms is 0. This is consistent with the findings of Fama

and French (2001) who report that firms have become less likely to pay dividends and the

proportion of dividend payers decreases, due in part to the changing firm characteristics.

The descriptive statistics show the negative trend for debt and payout ratios; however, cash

holdings tend to increase over the sample period. This provides the initial support for our

hypotheses. However, we find that the ratios based on book value of assets and ratios based on

market value of assets have different evolutions over time. One possible explanation is the

decreasing book-to-market ratio (book value of assets divided by market value of assets). Table

IV reports the book-to-market ratio, winsorized at the tails of 1% and 99%, in each year. The

mean (median) book-to-market ratio is 0.851 (0.895) in 1980 and decreases to 0.696 (0.683) in

2009. We also find that on average, high-tech firms have lower book-to-market ratio than non

high-tech firms; however, the gap between the two ratios erodes over time. Thus, the decreasing

book-to-market ratio is indeed one of the possible explanations for the differences between the

ratios based on book value of assets and ratios based on market value of assets.

[Insert Table IV here]

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III. Results

In this section, we test our hypotheses. First of all, we analyze the impact of institutional

ownership on firms’ leverage. Then we investigate whether payout ratio is affected by the

increase in institutional ownership. Further, we test the individual and combined effects of the

changes in Top5 holdings, leverage, and payout ratio on firms’ cash balances. At last, we test

whether greater cash balances enhance firm value.

A. The Impact of Institutional Ownership on Leverage

To test whether there is a negative relationship between leverage and concentrated institutional

ownership, we estimate the regressions similar to those used in Chang and Dasgupta (2009),

Fama and French (2002), Flannery and Rangan (2006), and Lemmon, Roberts, and Zender

(2008). Specifically, our benchmark models are:

0 1 2 3 4

5 6 7 7

Market leverage Top5 holdings HT dummy Ln Assets B/M

EBIT/Assets PPE/Assets R&D/Assets R&D dummy ;

t t t t t

tt t t t

(1)

0 1 2 3 4

5 6 7 7

Book leverage Top5 holdings HT dummy Ln Assets B/M

EBIT/Assets PPE/Assets R&D/Assets R&D dummy ,

t t t t t

tt t t t

(2)

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where HT dummy is equal to one if a firm is from the high-tech industries and zero otherwise.

Assets denotes book value of assets. B/M is book-to-market ratio. EBIT is earnings before

interests and taxes (the sum of income before extraordinary items (Compustat item IB), interest

and related expense (Compustat item XINT), and income taxes (Compustat item TXT)). PPE is

net property, plant, and equipment (Compustat item PPENT). R&D is research and development

expense (Compustat item XRD). R&D dummy is equal to one when R&D expense is unreported

in Compustat and zero otherwise. To reduce the impact of outliers and potential errors in

Compustat, we winsorize variables EBIT/Assets and R&D/Assets at the tails of 1% and 99%.

Further, PPE/Assets is winsorized so that it is between zero and one. The models include year

fixed effects.7 The standard errors are corrected for clustering at the firm level.

Table V presents the results. Model 1 and Model 2 show the results for Equations (1) and (2),

respectively. We find that both leverage measures are negatively impacted by concentrated

institutional ownership. The results are statistically and economically significant. The average

Top5 holdings have increased by 16.6 p.p. (0.214 – 0.048 = 0.166) over the sample period. The

coefficient estimate of Top5 holdings for market leverage is approximately –0.139. Thus, the

impact of the increase in Top5 holdings on average market leverage is –0.023 (0.166 * (–0.139)

= –0.023), ceteris paribus. It accounts for one third of the average decrease in market leverage as

the mean market leverage has decreased by 0.072 (0.159 – 0.231 = –0.072). The coefficient

estimate of Top5 holdings for book leverage is approximately –0.175. Similarly, the impact on

7 In our main models, we do not include industry fixed effects as it is likely that the effect of the industry might have

changed during 30-year time period. In other words, the impact of a particular industry in 1980 might be different

from the impact in 2009. For robustness, we repeat all our empirical tests with industry fixed effects defined by two-

digit SIC codes and find similar results.

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book leverage is –0.029 (0.166 * (–0.175) = –0.029) whereas the mean book leverage has

increased by 0.018 (0.287 – 0.269 = 0.018) during the 1980-2009 period. We also find that high-

tech firms have less debt. The signs and significance of the coefficients of other control variables

are similar to those reported in previous studies (see, for example, Chang and Dasgupta (2009),

Fama and French (2002), and Flannery and Rangan (2006)). The results support our Hypothesis

1.

[Insert Table V here]

It is possible that leverage and institutional ownership are interrelated with each other. To control

for endogeneity, we follow Harford, Mansi, and Maxwell (2008) and first estimate Model 3 and

Model 4 whose dependent variables are lead values of market leverage and book leverage. The

results are similar to those for Model 1 and Model 2. Secondly, we include lagged values of

leverage into the models (Model 5 and Model 6). In this specification, the coefficient estimates

for institutional ownership are still positive and statistically significant; however, their values

have become smaller.8

8 Another approach to control for endogeneity is two-stage least squares. However, the suitability of this method

depends on the availability of instrumental variables. Unfortunately, empirical studies that analyze institutional

ownership and firm capital structure (as well as cash holdings and payout policy) use similar control variables. Thus,

in our paper, we do not use two-stage least squares models. Recent empirical study by Harford, Mansi, and Maxwell

(2008) discusses this issue in more details.

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Franzen, Rodgers, and Simin (2009) report a negative relationship between off-balance sheet

lease financing and leverage. So it is entirely conceivable that the decrease in leverage is

observed as it has been substituted by the greater off-balance sheet lease financing. Following

Franzen, Rodgers, and Simin (2009), we construct a proxy for lease financing, Lease/Assets. It is

equal to the present value of non-cancelable operating leases divided by book value of assets.9 If

lease financing is unreported or missing on Compustat, we assume it is 0. We winsorize variable

Lease/Assets at the tails of 1% and 99%. Model 7 re-estimates Model 1 with the variable

Lease/Assets. We find the off-balance sheet lease financing does not impact leverage. The other

coefficient estimates are the same as in Model 1. To conclude, Table V provides the convincing

results that one of the reasons why leverage has decreased over the sample period is the

substantial increase in institutional ownership.

B. The Impact of Institutional Ownership on Payout Ratio

In this section, we test the impact of concentrated institutional ownership on firms’ payout ratio.

We estimate the model similar to one used in Fama and French (2001) and Fenn and Liang

(2001):

9 Franzen, Rodgers, and Simin (2009) compute the present value of non-cancelable operating leases as the

discounted sum of lease payments (Rental Expense (Compustat item XRENT) + 1/1.1 * Rental Commitments

Minimum 1st Year (Compustat item MRC1) + 1/(1.1)

2 * Rental Commitments Minimum 2

nd Year (Compustat item

MRC2) + 1/(1.1)3 * Rental Commitments Minimum 3

rd Year (Compustat item MRC3) + 1/(1.1)

4 * Rental

Commitments Minimum 4th

Year (Compustat item MRC4) + 1/(1.1)5 * Rental Commitments Minimum 5

th Year

(Compustat item MRC5), where 1.1 is a discount factor).

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0 1 2 3 4

5 6 7

Payout ratio Top5 holdings HT dummy Ln Assets B/M

Assets growth EBIT/Assets Book leverage ,

t t t t t

tt t t

(3)

where Assets growth is the annual growth rate of book value of assets. A variable Assets growth

is winsorized so that it is not greater than 1. The model includes year fixed effects and standard

errors are corrected for clustering at the firm level.

Model 1 of Table VI presents the results for Equation (3). We find that the impact of institutional

ownership on payout ratio is negative and statistically significant supporting our Hypothesis 2.

The change in average payout ratio over the sample period is –0.024 (0.031 – 0.055 = –0.024).

The coefficient estimate for Top5 holdings is approximately –0.06; therefore, the effect of the

increase in Top5 holdings on average payout ratio is –0.01 (–0.06 * 0.166 = –0.01) and it

accounts for almost 42% of the change in average payout ratio over the sample period. Thus, the

results are economically significant. We find that payout ratio tends to be smaller for high-tech

firms. It is consistent with Fama and French (2001) study which reports that small firms with low

profitability and strong growth opportunities are less likely to pay dividends. Consistent with

Fama and French (2001), we also find that larger, low-growth, and firms with greater book-to-

market ratio tend to have higher payout ratio. However, we find that profitability is negatively

related to payout ratio and it is in contrast to Fama and French (2001), presumable because Fama

and French (2001) use only dividends in their analysis. The results show that book leverage is

positively related to payout ratio. This implies that debt and payout policies are not substitutes in

mitigating agency costs of free cash flow but rather complements. One might argue that book

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leverage is endogenous because many empirical studies use dividends as one of the independent

variables for explaining leverage and find that dividend payers tend to have less debt (see, for

example, Lemmon, Roberts, and Zender (2008)). Thus, Model 2 re-estimates Model 1 without

book leverage. The coefficient estimates are consistent with those of Model 1. For robustness,

we re-estimate Model 1 and Model 2 with lead values of payout ratio as the dependant variable

(see Model 3 and Model 4). The results are consistent with the previous findings.

[Insert Table VI here]

C. The Determinants of Cash Holdings

To test Hypotheses 3 and 4, we estimate the regressions similar to those used in Opler et al.

(1999) and Bates, Kahle, and Stulz (2009). Specifically, our benchmark models are:

0 1 2 3

4 5 6 7

8 9 10 11

12 13

Market cash ratio Top5 holdings HT dummy Ln Assets

NWC/Assets Industry sigma FCF/Assets B/M

CAPEX/Assets R&D/Assets R&D dummy Book leverage

Dividend dummy

t t t t

t t t t

t t t t

t

14

15

Debt issuance/Assets Equity issuance/Assets

Acquisitions/Assets ;

t t

tt

(4)

20

0 1 2 3

4 5 6 7

8 9 10 11

12 13

Book cash ratio Top5 holdings HT dummy Ln Assets

NWC/Assets Industry sigma FCF/Assets B/M

CAPEX/Assets R&D/Assets R&D dummy Book leverage

Dividend dummy De

t t t t

t t t t

t t t t

t

14

15

bt issuance/Assets Equity issuance/Assets

Acquisitions/Assets ,

t t

tt

(5)

where NWC/Assets is the net working capital scaled by total assets (the difference between

working capital (Compustat item WCAP) and cash and short-term investments divided by book

value of assets). Industry sigma is the mean of the standard deviations of cash flow (operating

income before depreciation (Compustat item OIBDP) – interest and related expense – income

taxes) to book value of assets ratio over 10 years (if there are at least three observations) for

firms in the same industry, as defined by the two-digit SIC code. FCF/Assets is free cash flow

(operating income before depreciation – interest and related expense – income taxes – common

stock dividends (Compustat item DVC)) to book value of assets ratio. CAPEX/Assets is capital

expenditures (Compustat item CAPX) to book value of assets ratio. Dividend dummy is equal to

one if common stock dividends are positive and zero otherwise. Debt issuance/Assets is the

difference between long-term debt issuance (Compustat item DLTIS) and long-term debt

reduction (Compustat item DLTR) divided by book value of assets. Equity issuance/Assets is the

difference between sale of common and preferred stock (Compustat item SSTK) and purchase of

common and preferred stock divided by book value of assets. Acquisitions/Assets is acquisitions

(Compustat item AQC) divided by book value of assets. The variables FCF/Assets,

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CAPEX/Assets, Debt issuance/Assets, and Equity issuance/Assets are winsorized at the tails of

1% and 99%. NWC/Assets is winsorized so that it is greater than –1.

We include NWC/Assets into the models as it is entirely conceivable that one type of current

assets (cash) substituted other types of current assets (net working capital). Industry sigma

controls for cash flow risk. We expect that firms operating in the riskier industries hold more

cash (see Opler et al. (1999)). Further, we expect that cash holdings increase with FCF/Assets,

Debt issuance/Assets, and Equity issuance/Assets; however, are negatively affected by greater

Acquisitions/Assets and CAPEX/Assets. R&D/Assets is a proxy for growth opportunities. We

expect that firms with better growth opportunities hold more cash. The models also include year

fixed effects. The standard errors are corrected for clustering at the firm level.

Table VII presents the results. Model 1 shows the coefficient estimates where the dependent

variable is market cash ratio (Equation (4)) and Model 2’s dependent variable is book cash ratio

(Equation (5)). We find that cash holdings are positively related to Top5 holdings. The results

are statistically and economically significant. The average market cash ratio has increased by

0.056 (0.132 – 0.076 = 0.056) and the average book cash ratio has increased by 0.120 (0.226 –

0.106 = 0.120) over the sample period. The coefficient estimate of Top5 holdings for market

cash ratio is 0.043. Thus, the impact of the increase in Top5 holdings on market cash ratio is

0.007 (0.043 * 0.166 = 0.007). It corresponds to 13% of the increase in the average market cash

ratio during the last 30 years, ceteris paribus. The coefficient estimate of Top5 holdings for book

cash ratio is 0.089. The impact of the increase in Top5 holdings on market cash ratio is 0.015

22

(0.089 * 0.166 = 0.015). It accounts for 12% of the change in the average book cash ratio during

the last 30 years. Thus, the results support our Hypothesis 3.

[Insert Table VII here]

We also find a negative and statistically significant relationship between cash balances and

leverage. This supports our Hypothesis 4 as lower leverage implies greater cash holdings. We

find that high-tech firms hold more cash on average. The sign and significance of other variables

are similar to those documented in prior studies (see, for example, Opler et al. (1999) and Bates,

Kahle, and Stulz (2009)).

Model 3 and Model 4 re-estimate Model 1 and Model 2 using Payout ratio as the additional

independent variable. We document the negative relationship between cash holdings and payout

ratio. The result is consistent across both models and supports our Hypothesis 5.

For robustness, we re-estimate Model 1 and Model 2 with lead values of cash holdings as the

dependent variables (see Model 5 and Model 6). The results are similar to those reported earlier

and support our hypotheses that cash holdings increase with institutional ownership and decrease

with leverage. At last, we investigate whether our conclusion holds after controlling for the effect

of predation risk. Following Haushalter, Klasa, and Maxwell (2007), we replicate Model 1 using

Herfindahl-Hirschman Index as the additional independent variable. Herfindahl-Hirschman

Index is a measure of product market competition and is calculated using sales data of individual

23

firms in the same industry, as defined by the four-digit SIC code.10

Model 7 in Table VII shows

the coefficient estimates for the regression. We find that institutional ownership and leverage are

still significant determinants of cash holdings after controlling for Herfindahl-Hirschman Index.

However, in contrast to Haushalter, Klasa, and Maxwell (2007), the results show that firms

operating in more competitive industries hold more cash.11

To conclude, the results presented in Table VII support our Hypotheses 3, 4, and 5. We show

that the changes in cash ratios are due in part to the changes in institutional ownership, leverage,

and payout policy. Further, we test Hypothesis 6.

D. The Impact on Firm Value

The results above support our first five hypotheses. However, it does not imply that we find

support for free cash flow hypothesis. We argue that firms should rationally increase their cash

holdings if agency problem of free cash flow is reduced. As the goal of firm management is to

10 Herfindahl-Hirschman Index (HHI) is computed as follows:

i

i

i

i

Sales

Sales

HHI2

2

)(, where Salesi denotes sales

of firm i in a particular industry. 11

As a robustness check, we also use Herfindahl-Hirschman Index calculated assuming that industry is defined by

the two-digit SIC code. In this specification, we find that coefficient estimate for Herfindahl-Hirschman Index is

positive but insignificant. We also re-estimate the models using Book cash ratio as the dependent variable. We find

that the coefficient estimate for Herfindahl-Hirschman Index is negative and statistically significant, disregarding

how we compute Herfindahl-Hirschman Index. Results are available upon request.

24

maximize shareholder value, this rational increase in cash holdings should eventually lead to

greater firm value. In this section, we test this issue (Hypothesis 6).

We use Tobin’s q as a proxy for firm value. Then we estimate the following model:

0 1 2 3 4

5 6 7 8

10

Q Top5 holdings HT dummy Ln Assets Book leverage

Book cash ratio EBIT/Assets PPE/Assets CAPEX/Assets

Dividend dummy ,

t t t t t

t t t t

tt

(6)

where Q is Tobin’s q (market value of assets divided by book value of assets) winsorized at tails

of 1% and 99%. The selection of independent variables is based on the prior studies (see, for

example, Coles, Daniel, and Naveen (2008), Kalcheva and Lins (2007)). The model includes

year fixed effects. Standard errors are corrected for clustering at the firm level.

Model 1 in Table VIII reports the results for Equation (6). We find that cash holdings are

positively associated with firm value proxied by Tobin’s q after controlling for firm

characteristics. It supports Hypothesis 6 that greater cash balances enhance firm value. The

results suggest that greater institutional ownership further increases the firm value. In addition,

the results show that high-tech firms are more likely to have a greater Tobin’s q. Leverage

enhances firm value, presumably due to the additional risk associated with debt and additional

monitoring provided by debtholders. We also find the negative relationship between firm size

and Tobin’s q; however, dividends and capital expenditures tend to improve firm value.

[Insert Table VIII here]

25

Model 2 re-estimates Model 1 using lead values of Tobin’s q as the dependent variable. The

results qualitatively are the same as those in Model 1 and further support Hypothesis 6. We re-

estimate Model 2 using Tobin’s q as an additional independent variable. Model 3 in Table VIII

presents the results that are consistent with our previous findings except the coefficient estimate

for Top5 holdings is insignificant. In Model 4, we replace Dividend dummy with Payout ratio

and test whether decrease in payout ratio improves firm value. We find that the coefficient

estimate for Payout ratio is negative and statistically significant providing support for our

prediction.

When firm’s cash holdings are low, an increase in institutional concentration (monitoring) has

larger impact on the firm value. With the increase in monitoring (Top5 holdings), we would

expect that a firm will use its cash reserves more effectively. Therefore, we would expect that

each dollar has a higher value. However, Faulkender and Wang (2006) find that the value of

additional cash diminishes in the level of cash. Thus, the monitoring effect is subject to

diminishing marginal returns implying that the monitoring effect is greater when the initial cash

balance is smaller, and vice versa. In other words, keeping the same monitoring level, each

incremental unit of cash will have smaller impact on the improving firm value. Thus, at last we

test whether monitoring effect is indeed non-linear. Model 5 re-estimates Model 1 with the

interaction term of Top5 holdings and Book cash ratio. We expect that the coefficient estimate

for Top5 holdings will be positive and the coefficient estimate for the interaction term will be

26

negative. The results presented in Table VIII show that the marginal effect of Top5 holdings on

cash value is decreasing with the increase of cash reserves. The results support our view.

It is possible that the impact of Top5 holdings on firm and cash values is not instantaneous.

Model 6 re-estimates Model 5 using lead values of Tobin’s q as the dependent variable. The

results are economically and statistically similar.

Then we perform a sensitivity analysis. We calculate hypothetical lead values of Tobin’s q using

the coefficient estimates of Model 6 with different values of Top5 holdings and Book cash ratio,

and mean values of other variables. Then we calculate the difference between the computed

numbers and the hypothetical lead value of Tobin’s q that is computed using the coefficient

estimates of Model 6 and mean values of all variables including Top5 holdings and Book cash

ratio. The positive (negative) difference shows a greater (lower) firm value. Table IX presents

the results. We find that greater cash holdings improve firm value at any level of Top5 holdings.

However, the effect of Top5 holdings on firm value is nonlinear. In the last column (Diff.) of

Table IX, we calculate the incremental impact on firm value when Book cash ratio increases

from 0 to 0.4. We find that cash balances have greater effect on firm value when concentrated

institutional ownership is smaller. Top5 holdings enhance firm value when Book cash ratio is

less than 0.3 or 157% of the mean of Book cash ratio.12

This suggests that in most cases greater

Top5 holdings improve firm value. However, if Book cash ratio is greater than 0.3 then there is a

negative relationship between firm value and concentrated institutional ownership.

12

The mean of Book cash ratio is 0.175.

27

[Insert Table IX here]

In summary, we show that the increased institutional ownership translates into the lower leverage

and payout ratio that consequently lead to greater cash holdings and firm value. The results

provide strong support for the free cash flow hypothesis and help explain the evolution of

leverage, cash holdings, and payout ratio during the last 30 years.

E. Robustness Checks

We perform several robustness checks.13

First of all, we re-estimate all models separately for

high-tech and non high-tech firms as one might argue that these two sectors have evolved

differently over the sample period. However, the results for both types of firms are similar to

those previously reported and further support our hypotheses. We also repeat our empirical tests

with industry fixed effects defined by two-digit SIC codes. All the results hold.

Then we re-estimate all models using total institutional ownership instead of Top5 holdings and

get similar results.

13

The untabulated results are available upon request.

28

In all models, we use ln(Assets) as our firm size proxy. The sample spans over a 30-year period.

Thus, one might argue that our results are systematically biased as firm size tends to increase

over time. We repeat all our tests using the percentile of book value of assets as a proxy for firm

size. The results are essentially unchanged.

Opler et al. (1999) and Haushalter, Klasa, and Maxwell (2007) run the regressions where the

dependent variable is the natural logarithm of the sum of cash and short-term investments

divided by book assets minus cash and short-term investments. Similarly, Harford, Mansi, and

Maxwell (2008) use the natural logarithm of cash-to-sales ratio as a proxy for cash holdings. For

robustness, we repeat all the tests using the natural logarithm of book cash ratio and market cash

ratio as the dependent variables and find similar results.

At last, to make sure that endogeneity is not affecting our results, we estimate three-stage least

squares model. The dependent variables are book leverage, payout ratio, and book cash ratio.

The potential endogenous variables are book leverage and payout ratio.14

The instrumental

variable for book leverage is net property, plant, and equipment scaled by book value of assets.

The instrumental variable for payout ratio is assets growth. The results are similar to those

reported in Tables V-VII except the coefficient estimate for Top5 holdings in Book cash ratio

equation is significant only at 0.115 level (see Table X).15

Thus, the results support our

Hypotheses 1-5.

14

It is also likely that Tobin’s q (inverse Book-to-market ratio) might be endogenous. However, we do not include

Tobin’s q equation into the simultaneous equation model as all the exogenous control variables in the Tobin’s q

equation are also included in the other models. Thus, Tobin’s q would be unidentified. 15

If we replace Top5 holdings with total institutional ownership, we get that the coefficient estimate for total

29

[Insert Table X here]

IV. Conclusion

This paper tests the free cash flow hypothesis and documents the impact of the dramatic increase

in institutional ownership on key firm characteristics. We argue that greater institutional

ownership, measured as the ownership controlled by five largest institutional investors, reduces

the agency problem of free cash flow. To test our hypothesis, we use a large data sample that

spans over a 30-year time period.

The results reveal the channels of value creation. We find that the increased institutional

ownership substitutes other mechanisms that reduce agency problem associated with excess cash

flow. Thus, we observe the decrease in debt and payout ratios. Due to the effective monitoring of

institutional investors, lower debt and payout ratios lead to greater cash holdings rather than to

the value-destroying investments. At last, greater cash balances reduce underinvestment and

predation risks and thus increase firm value. All our tests support these findings.

The results of this paper contribute to our better understanding of the role of institutional

investors in monitoring firm managers and in the process of shareholder wealth maximization.

institutional ownership is significant at 0.001 level and consistent with our main results.

30

The presence of institutional investors enhances firm value directly and indirectly (via greater

cash holdings and reduced underinvestment and predation risks).

The sample that spans over 30-year time period provides an excellent opportunity to investigate

the long-term impact of the change in ownership structure and improved monitoring on key firm

characteristics. Our paper contributes to three different strands of literature. First of all, our

results show that one of the reasons for decreasing payout over time is increased institutional

ownership.16

Secondly, we show that the change in ownership structure is one of the reasons for

decreasing leverage. Thirdly, we provide the alternative explanation for the increased cash

holdings.17

We argue that cash balances increase due to improved monitoring. This suggests that

firms hold less than optimal cash in absence of effective monitoring by shareholders.

To conclude, this paper supports the free cash flow hypothesis. We find that the dramatic

increase in institutional ownership (from 7.3% to 45.7%) during the period 1980 through 2009

positively affects cash holdings of U.S. firms; however, the impact of institutional ownership on

leverage and payout ratio is negative. The results are robust to a number of alternative

specifications.

16

The recent papers that concern this issue include DeAngelo, DeAngelo, and Skinner (2004), Fama and French

(2001), and Grullon and Michaely (2002). 17

Bates, Kahle, and Stulz (2009), Faulkender and Wang (2006), Harford, Mansi, and Maxwell (2008), Haushalter,

Klasa, and Maxwell (2007), and Opler et al. (1999) investigate this issue.

31

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36

Figure 1. Hypotheses. This figure plots our hypotheses. Hypothesis 1 (H1): Higher ownership

controlled by five largest institutional investors (Top5 holdings) will be associated with lower

leverage. H2: Higher ownership controlled by five largest institutional investors will be

associated with lower payout ratio. H3: Higher ownership controlled by five largest institutional

investors will be associated with higher cash holdings. H4: There will be a negative relationship

between cash holdings and leverage. H5: There will be a negative relationship between cash

holdings and payout ratio. H6: Cash holdings will be positively associated with firm value.

37

Table I

Institutional Ownership

This table shows the institutional ownership from 1980 to 2009. The sample consists of all Compustat

firm-year observations during the period 1980 through 2009. We eliminate financial firms (with

Standard Industrial Classification (SIC) codes 6000-6999) and public utility firms (with SIC codes

4900-4999). Firms must have positive assets (Compustat item AT), positive sales (Compustat item

SALE), positive common shares outstanding (Compustat item CSHO), positive closing share price at

the end of the fiscal year (Compustat item PRCC_F) and be incorporated in the United States of

America. Industry (high-tech vs. non high-tech) is defined according to the definition of TechAmerica.

Institutional ownership is the percentage of shares held by institutional investors. We assume that firms

not covered by Thomson Reuters have no institutional investors. N is the number of observations.

High-tech firms ratio is the number of high-tech firms over the number of all firms in each year.

All firms Non high-tech firms High-tech firms High-tech

Year N Mean Median N Mean Median N Mean Median firms ratio

1980 3,678 0.073 0.000 3,136 0.073 0.000 542 0.073 0.000 0.147

1981 4,194 0.070 0.000 3,529 0.070 0.000 665 0.070 0.000 0.159

1982 4,169 0.077 0.000 3,467 0.076 0.000 702 0.083 0.000 0.168

1983 4,482 0.091 0.000 3,628 0.089 0.000 854 0.099 0.000 0.191

1984 4,517 0.098 0.000 3,600 0.096 0.000 917 0.106 0.003 0.203

1985 4,423 0.112 0.003 3,477 0.111 0.002 946 0.116 0.008 0.214

1986 4,552 0.120 0.004 3,569 0.117 0.002 983 0.131 0.014 0.216

1987 4,670 0.125 0.007 3,647 0.123 0.007 1,023 0.132 0.011 0.219

1988 4,427 0.132 0.013 3,451 0.132 0.011 976 0.130 0.016 0.220

1989 4,265 0.141 0.014 3,327 0.141 0.013 938 0.139 0.018 0.220

1990 4,195 0.152 0.018 3,271 0.153 0.014 924 0.149 0.032 0.220

1991 4,233 0.160 0.018 3,317 0.161 0.016 916 0.156 0.029 0.216

1992 4,441 0.177 0.041 3,467 0.181 0.044 974 0.162 0.034 0.219

1993 4,768 0.180 0.061 3,704 0.184 0.068 1,064 0.168 0.044 0.223

1994 5,026 0.198 0.074 3,920 0.200 0.078 1,106 0.188 0.066 0.220

1995 5,619 0.198 0.061 4,289 0.202 0.064 1,330 0.186 0.046 0.237

1996 6,126 0.193 0.059 4,609 0.198 0.060 1,517 0.181 0.057 0.248

1997 6,183 0.216 0.084 4,615 0.223 0.090 1,568 0.193 0.073 0.254

1998 5,997 0.223 0.088 4,467 0.233 0.099 1,530 0.193 0.053 0.255

1999 6,066 0.214 0.077 4,445 0.222 0.088 1,621 0.191 0.055 0.267

2000 5,944 0.223 0.075 4,285 0.231 0.081 1,659 0.202 0.060 0.279

2001 5,489 0.246 0.083 3,966 0.254 0.098 1,523 0.224 0.059 0.277

2002 5,075 0.277 0.121 3,672 0.288 0.142 1,403 0.248 0.084 0.276

2003 4,756 0.304 0.176 3,441 0.316 0.204 1,315 0.274 0.116 0.276

2004 4,656 0.358 0.256 3,361 0.373 0.289 1,295 0.319 0.178 0.278

2005 4,481 0.389 0.335 3,252 0.403 0.362 1,229 0.351 0.250 0.274

2006 4,368 0.423 0.388 3,217 0.438 0.425 1,151 0.380 0.297 0.264

2007 4,221 0.456 0.443 3,118 0.470 0.482 1,103 0.416 0.358 0.261

2008 3,925 0.459 0.469 2,920 0.469 0.488 1,005 0.430 0.421 0.256

2009 3,512 0.457 0.479 2,639 0.464 0.498 873 0.436 0.449 0.249

38

Table II

Mean and Median Cash Ratios from 1980 to 2009

This table shows cash holdings from 1980 to 2009. Market cash ratio is cash and short-term

investments (Compustat item CHE) over market value of assets (book value of assets (Compustat item

AT) – common equity (Compustat item CEQ) + common shares outstanding (Compustat item CSHO) *

closing share price at the end of the fiscal year (Compustat item PRCC_F)). Book cash ratio is cash and

short-term investments over book value of assets. Industry (high-tech vs. non high-tech) is defined

according to the definition of TechAmerica.

Market cash ratio Book cash ratio

All firms Non high-tech firms High-tech firms All firms Non high-tech firms High-tech firms

Year Mean Median Mean Median Mean Median Mean Median Mean Median Mean Median

1980 0.076 0.043 0.077 0.044 0.069 0.036 0.106 0.055 0.103 0.055 0.123 0.056

1981 0.092 0.048 0.092 0.047 0.094 0.054 0.121 0.058 0.114 0.054 0.158 0.092

1982 0.092 0.050 0.093 0.049 0.087 0.050 0.122 0.064 0.115 0.060 0.157 0.092

1983 0.095 0.056 0.094 0.053 0.099 0.066 0.156 0.085 0.142 0.075 0.218 0.144

1984 0.095 0.049 0.094 0.048 0.099 0.051 0.138 0.068 0.130 0.063 0.170 0.090

1985 0.088 0.046 0.085 0.044 0.098 0.054 0.140 0.069 0.131 0.063 0.176 0.104

1986 0.095 0.048 0.091 0.046 0.109 0.066 0.154 0.079 0.145 0.070 0.188 0.119

1987 0.104 0.050 0.098 0.046 0.127 0.071 0.153 0.074 0.140 0.066 0.196 0.122

1988 0.094 0.044 0.088 0.040 0.116 0.060 0.138 0.066 0.127 0.059 0.176 0.098

1989 0.089 0.041 0.083 0.037 0.109 0.054 0.135 0.060 0.126 0.053 0.167 0.091

1990 0.098 0.043 0.090 0.039 0.123 0.064 0.132 0.059 0.121 0.052 0.172 0.094

1991 0.091 0.044 0.085 0.040 0.112 0.067 0.152 0.069 0.141 0.060 0.190 0.122

1992 0.091 0.046 0.083 0.041 0.119 0.070 0.159 0.076 0.145 0.065 0.210 0.133

1993 0.089 0.046 0.080 0.040 0.118 0.079 0.169 0.081 0.148 0.066 0.242 0.173

1994 0.089 0.042 0.081 0.036 0.114 0.078 0.153 0.069 0.134 0.055 0.222 0.164

1995 0.081 0.039 0.074 0.032 0.105 0.070 0.167 0.069 0.140 0.052 0.254 0.186

1996 0.091 0.045 0.082 0.037 0.119 0.078 0.188 0.083 0.160 0.063 0.270 0.206

1997 0.094 0.044 0.084 0.035 0.121 0.079 0.187 0.086 0.159 0.061 0.268 0.212

1998 0.100 0.041 0.089 0.033 0.133 0.073 0.175 0.071 0.149 0.052 0.251 0.185

1999 0.082 0.035 0.076 0.029 0.101 0.054 0.197 0.079 0.161 0.053 0.297 0.225

2000 0.120 0.045 0.103 0.033 0.165 0.089 0.201 0.083 0.166 0.054 0.290 0.225

2001 0.123 0.050 0.103 0.038 0.173 0.097 0.203 0.096 0.171 0.066 0.285 0.222

2002 0.149 0.062 0.122 0.048 0.218 0.134 0.203 0.104 0.168 0.074 0.293 0.244

2003 0.106 0.058 0.093 0.046 0.140 0.099 0.220 0.125 0.187 0.090 0.309 0.261

2004 0.106 0.062 0.092 0.049 0.143 0.106 0.234 0.140 0.203 0.102 0.315 0.277

2005 0.106 0.062 0.093 0.050 0.141 0.104 0.231 0.141 0.204 0.104 0.301 0.266

2006 0.103 0.060 0.092 0.049 0.135 0.094 0.231 0.132 0.208 0.099 0.295 0.244

2007 0.110 0.061 0.098 0.049 0.144 0.101 0.223 0.123 0.200 0.092 0.290 0.236

2008 0.151 0.080 0.130 0.063 0.210 0.136 0.204 0.114 0.182 0.091 0.268 0.215

2009 0.132 0.085 0.117 0.073 0.177 0.130 0.226 0.146 0.205 0.121 0.291 0.250

39

Table III

Mean and Median Debt Ratios from 1980 to 2009

This table shows leverage from 1980 to 2009. Market leverage is debt (the sum of long-term debt

(Compustat item DLTT) and debt in current liabilities (Compustat item DLC)) over market value of

assets (book value of assets (Compustat item AT) – common equity (Compustat item CEQ) + common

shares outstanding (Compustat item CSHO) * closing share price at the end of the fiscal year

(Compustat item PRCC_F)). Book leverage is debt over book value of assets. Industry (high-tech vs.

non high-tech) is defined according to the definition of TechAmerica.

Market leverage Book leverage

All firms Non high-tech firms High-tech firms All firms Non high-tech firms High-tech firms

Year Mean Median Mean Median Mean Median Mean Median Mean Median Mean Median

1980 0.231 0.198 0.243 0.213 0.167 0.124 0.269 0.245 0.272 0.250 0.250 0.221

1981 0.231 0.200 0.244 0.219 0.163 0.104 0.263 0.231 0.270 0.239 0.226 0.171

1982 0.231 0.195 0.245 0.215 0.159 0.104 0.276 0.237 0.283 0.245 0.243 0.178

1983 0.187 0.141 0.203 0.161 0.117 0.056 0.252 0.207 0.263 0.219 0.204 0.132

1984 0.209 0.171 0.224 0.188 0.152 0.102 0.267 0.221 0.275 0.234 0.234 0.171

1985 0.207 0.166 0.222 0.185 0.152 0.101 0.282 0.235 0.291 0.248 0.249 0.184

1986 0.205 0.162 0.219 0.180 0.155 0.102 0.289 0.244 0.301 0.259 0.247 0.176

1987 0.217 0.175 0.231 0.192 0.168 0.115 0.289 0.247 0.300 0.262 0.252 0.187

1988 0.220 0.176 0.232 0.191 0.176 0.127 0.291 0.248 0.300 0.261 0.259 0.197

1989 0.221 0.176 0.234 0.192 0.177 0.122 0.296 0.258 0.305 0.270 0.264 0.197

1990 0.237 0.191 0.251 0.208 0.190 0.126 0.293 0.247 0.301 0.260 0.265 0.181

1991 0.203 0.146 0.217 0.165 0.154 0.086 0.268 0.220 0.279 0.239 0.230 0.136

1992 0.180 0.125 0.194 0.143 0.131 0.061 0.249 0.198 0.260 0.221 0.209 0.114

1993 0.157 0.109 0.171 0.127 0.106 0.046 0.233 0.184 0.247 0.210 0.184 0.089

1994 0.165 0.119 0.183 0.142 0.104 0.044 0.233 0.189 0.252 0.219 0.167 0.085

1995 0.165 0.111 0.187 0.143 0.095 0.027 0.247 0.195 0.270 0.230 0.171 0.074

1996 0.157 0.099 0.177 0.127 0.098 0.030 0.247 0.180 0.268 0.215 0.183 0.067

1997 0.161 0.100 0.180 0.129 0.103 0.032 0.263 0.192 0.284 0.228 0.200 0.080

1998 0.192 0.130 0.214 0.164 0.126 0.048 0.292 0.214 0.310 0.251 0.239 0.104

1999 0.184 0.107 0.216 0.160 0.096 0.019 0.295 0.211 0.317 0.253 0.235 0.077

2000 0.191 0.112 0.221 0.153 0.115 0.026 0.296 0.190 0.323 0.240 0.224 0.060

2001 0.183 0.109 0.207 0.143 0.120 0.034 0.327 0.194 0.345 0.238 0.278 0.074

2002 0.188 0.123 0.209 0.156 0.133 0.048 0.327 0.190 0.338 0.230 0.300 0.079

2003 0.150 0.084 0.171 0.117 0.095 0.020 0.313 0.179 0.327 0.217 0.275 0.056

2004 0.132 0.074 0.149 0.104 0.087 0.015 0.295 0.159 0.310 0.196 0.255 0.047

2005 0.132 0.077 0.146 0.097 0.093 0.022 0.291 0.156 0.298 0.186 0.272 0.056

2006 0.132 0.077 0.145 0.096 0.096 0.029 0.298 0.158 0.300 0.186 0.295 0.070

2007 0.147 0.086 0.161 0.107 0.109 0.032 0.305 0.165 0.308 0.195 0.296 0.072

2008 0.201 0.136 0.219 0.163 0.148 0.059 0.328 0.186 0.332 0.219 0.316 0.090

2009 0.159 0.094 0.173 0.116 0.117 0.044 0.287 0.157 0.290 0.182 0.280 0.077

40

Table IV

Mean and Median Payout and Book-to-Market Ratios from 1980 to 2009

This table illustrates payout and book-to-market ratios from 1980 to 2009. Payout ratio is a sum of

common stock dividends (Compustat item DVC) and absolute value of the difference between

purchase of common and preferred stock (Compustat item PRSTKC) and preferred stock redemption

value (Compustat item PSTKRV) divided by market value of equity (common shares outstanding

(Compustat item CSHO) * closing share price at the end of the fiscal year (Compustat item PRCC_F)).

Book-to-market ratio is book value of assets (Compustat item AT) divided by market value of assets

(book value of assets – common equity (Compustat item CEQ) + common shares outstanding * closing

share price at the end of the fiscal). Industry (high-tech vs. non high-tech) is defined according to the

definition of TechAmerica.

Payout ratio Book-to-market ratio

All firms Non high-tech firms High-tech firms All firms Non high-tech firms High-tech firms

Year Mean Median Mean Median Mean Median Mean Median Mean Median Mean Median

1980 0.055 0.023 0.059 0.029 0.033 0.002 0.851 0.895 0.885 0.945 0.656 0.609

1981 0.053 0.017 0.057 0.024 0.030 0.000 0.879 0.906 0.912 0.949 0.702 0.674

1982 0.050 0.014 0.055 0.019 0.027 0.000 0.854 0.873 0.895 0.918 0.649 0.605

1983 0.039 0.007 0.043 0.012 0.021 0.000 0.729 0.733 0.772 0.783 0.546 0.503

1984 0.045 0.008 0.050 0.013 0.028 0.000 0.791 0.809 0.822 0.843 0.667 0.653

1985 0.043 0.006 0.047 0.011 0.029 0.000 0.741 0.755 0.768 0.784 0.642 0.619

1986 0.043 0.004 0.047 0.007 0.030 0.000 0.719 0.726 0.738 0.748 0.649 0.646

1987 0.049 0.006 0.051 0.010 0.040 0.000 0.768 0.780 0.785 0.801 0.707 0.714

1988 0.048 0.005 0.050 0.008 0.040 0.000 0.761 0.778 0.773 0.788 0.717 0.717

1989 0.047 0.004 0.049 0.007 0.040 0.000 0.748 0.753 0.760 0.767 0.705 0.689

1990 0.054 0.007 0.056 0.010 0.047 0.000 0.832 0.834 0.843 0.854 0.794 0.777

1991 0.044 0.002 0.047 0.005 0.035 0.000 0.741 0.733 0.754 0.754 0.695 0.664

1992 0.039 0.001 0.041 0.003 0.029 0.000 0.702 0.684 0.715 0.710 0.656 0.609

1993 0.034 0.000 0.037 0.002 0.024 0.000 0.647 0.628 0.665 0.654 0.581 0.535

1994 0.037 0.000 0.040 0.002 0.025 0.000 0.686 0.673 0.709 0.703 0.604 0.562

1995 0.037 0.000 0.039 0.001 0.027 0.000 0.644 0.618 0.683 0.673 0.517 0.459

1996 0.036 0.000 0.039 0.001 0.026 0.000 0.625 0.602 0.657 0.643 0.528 0.488

1997 0.037 0.001 0.038 0.002 0.032 0.000 0.613 0.587 0.644 0.626 0.519 0.478

1998 0.047 0.005 0.048 0.007 0.042 0.000 0.691 0.678 0.723 0.724 0.595 0.547

1999 0.045 0.003 0.050 0.008 0.029 0.000 0.636 0.619 0.705 0.726 0.446 0.351

2000 0.052 0.002 0.056 0.006 0.041 0.000 0.738 0.710 0.783 0.778 0.624 0.547

2001 0.044 0.001 0.046 0.002 0.040 0.000 0.704 0.667 0.735 0.715 0.622 0.549

2002 0.045 0.001 0.046 0.002 0.044 0.000 0.777 0.766 0.793 0.789 0.736 0.701

2003 0.035 0.000 0.035 0.001 0.035 0.000 0.595 0.576 0.631 0.628 0.502 0.462

2004 0.034 0.000 0.035 0.001 0.031 0.000 0.556 0.541 0.578 0.569 0.499 0.476

2005 0.037 0.000 0.038 0.003 0.035 0.000 0.560 0.543 0.575 0.563 0.520 0.501

2006 0.037 0.001 0.037 0.003 0.038 0.000 0.551 0.540 0.566 0.556 0.512 0.496

2007 0.044 0.002 0.044 0.004 0.044 0.000 0.598 0.576 0.615 0.593 0.550 0.534

2008 0.060 0.010 0.061 0.013 0.059 0.004 0.825 0.810 0.835 0.823 0.799 0.748

2009 0.031 0.001 0.030 0.002 0.033 0.000 0.696 0.683 0.712 0.707 0.647 0.620

41

Table V

Determinants of Market and Book Leverage

This table presents the results of least squares regressions where the dependent variable is either market

or book leverage. Market leverage is debt (the sum of long-term debt (Compustat item DLTT) and debt

in current liabilities (Compustat item DLC)) over market value of assets (book value of assets

(Compustat item AT) – common equity (Compustat item CEQ) + common shares outstanding

(Compustat item CSHO) * closing share price at the end of the fiscal year (Compustat item PRCC_F)).

Book leverage is debt over book value of assets. Top5 holdings is the ownership controlled by five

largest institutional investors. We assume that firms not covered by Thomson Reuters have no

institutional investors. High-tech dummy equals one if a firm is from high-tech (defined according to

the definition of TechAmerica), zero otherwise. Lease/Assets is equal to the present value of non-

cancelable operating leases divided by book value of assets. ln(Assets) is the natural logarithm of book

value of assets (in millions of U.S. dollars (converted into 2009 constant dollars using the GDP

deflator)). Book-to-market is book value of assets divided by market value of assets. EBIT/Assets is

earnings before interests and taxes (the sum of income before extraordinary items (Compustat item IB),

interest and related expense (Compustat item XINT), and income taxes (Compustat item TXT)) divided

by book value of assets. PPE/Assets is net property, plant, and equipment (Compustat item PPENT)

divided by book value of assets. R&D/Assets is research and development expense (Compustat item

XRD) divided by book value of assets. R&D dummy is equal to one when R&D expense is unreported

in Compustat and zero otherwise. p-values based on standard errors robust to clustering by firm are

reported in parentheses.

42

Table V (continued)

Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7

Dependant variable Market

leveraget Book

leveraget Market

leveraget+1 Book

leveraget+1 Market

leveraget+1 Book

leveraget+1 Market

leveraget

Market leveraget

0.834

(0.000)

Book leveraget

0.776

(0.000)

Top5 holdingst –0.139 –0.175 –0.134 –0.201 –0.024 –0.074 –0.139

(0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000)

High-tech dummyt –0.018 –0.019 –0.019 –0.017 –0.005 –0.001 –0.018

(0.000) (0.001) (0.000) (0.004) (0.000) (0.663) (0.000)

Lease/Assetst

–0.003

(0.631)

ln(Assets)t 0.013 0.004 0.012 0.004 0.001 –0.001 0.013

(0.000) (0.001) (0.000) (0.002) (0.000) (0.179) (0.000)

Book-to-market ratiot 0.127 –0.069 0.113 –0.054 –0.009 –0.012 0.127

(0.000) (0.000) (0.000) (0.000) (0.000) (0.020) (0.000)

EBIT/Assetst –0.048 –0.315 –0.048 –0.314 –0.005 –0.076 –0.048

(0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000)

PPE/Assetst 0.153 0.235 0.144 0.210 0.021 0.033 0.153

(0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000)

R&D/Assetst –0.153 –0.372 –0.177 –0.380 –0.049 –0.089 –0.153

(0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000)

R&D dummyt 0.032 0.051 0.033 0.050 0.008 0.014 0.032

(0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000)

Year fixed effects Yes Yes Yes Yes Yes Yes Yes

R2 0.236 0.207 0.209 0.168 0.703 0.574 0.236

Adjusted R2 0.236 0.207 0.208 0.168 0.703 0.574 0.236

Number of observations 141,693 141,693 126,464 126,474 126,346 126,356 141,693

43

Table VI

Determinants of Payout Ratio

This table presents the results of least squares regressions where the dependent variable is payout ratio.

Payout ratio is a sum of common stock dividends (Compustat item DVC) and absolute value of the

difference between purchase of common and preferred stock (Compustat item PRSTKC) and preferred

stock redemption value (Compustat item PSTKRV) divided by market value of equity (common shares

outstanding (Compustat item CSHO) * closing share price at the end of the fiscal year (Compustat item

PRCC_F)). Top5 holdings is the ownership controlled by five largest institutional investors. We assume

that firms not covered by Thomson Reuters have no institutional investors. High-tech dummy equals

one if a firm is from high-tech (defined according to the definition of TechAmerica), zero otherwise.

ln(Assets) is the natural logarithm of book value of assets (in millions of U.S. dollars (Compustat item

AT) (converted into 2009 constant dollars using the GDP deflator)). Book-to-market is book value of

assets divided by market value of assets (book value of assets (Compustat item AT) – common equity

(Compustat item CEQ) + common shares outstanding (Compustat item CSHO) * closing share price at

the end of the fiscal year (Compustat item PRCC_F)). Assets growth is the annual growth rate of book

value of assets. EBIT/Assets is earnings before interests and taxes (the sum of income before

extraordinary items (Compustat item IB), interest and related expense (Compustat item XINT), and

income taxes (Compustat item TXT)) divided by book value of assets. Book leverage is debt (the sum

of long-term debt (Compustat item DLTT) and debt in current liabilities (Compustat item DLC)) over

book value of assets. p-values based on standard errors robust to clustering by firm are reported in

parentheses.

Model 1 Model 2 Model 3 Model 4

Dependant variable Payout ratiot Payout ratiot Payout ratiot+1 Payout ratiot+1

Top5 holdingst –0.055 –0.062 –0.056 –0.061

(0.000) (0.000) (0.000) (0.000)

High-tech dummyt –0.005 –0.007 –0.005 –0.007

(0.000) (0.000) (0.000) (0.000)

ln(Assets)t 0.005 0.005 0.005 0.005

(0.000) (0.000) (0.000) (0.000)

Book-to-market ratiot 0.016 0.014 0.012 0.011

(0.000) (0.000) (0.000) (0.000)

Assets growtht –0.025 –0.025 –0.015 –0.015

(0.000) (0.000) (0.000) (0.000)

EBIT/Assetst –0.003 –0.011 –0.009 –0.016

(0.012) (0.000) (0.000) (0.000)

Book leveraget 0.026

0.023

(0.000)

(0.000)

Year fixed effects Yes Yes Yes Yes

R2 0.051 0.040 0.041 0.034

Adjusted R2 0.051 0.040 0.041 0.034

Number of observations 121,635 122,011 108,212 108,538

44

Table VII

Determinants of Cash Holdings

This table presents the results of least squares regressions where the dependent variable is either market

or book cash ratio. Market cash ratio is cash and short-term investments (Compustat item CHE)

divided by market value of assets (book value of assets (Compustat item AT) – common equity

(Compustat item CEQ) + common shares outstanding (Compustat item CSHO) * closing share price at

the end of the fiscal year (Compustat item PRCC_F)). Book cash ratio is cash and short-term

investments divided by book value of assets. Top5 holdings is the ownership controlled by five largest

institutional investors. We assume that firms not covered by Thomson Reuters have no institutional

investors. High-tech dummy equals one if a firm is from high-tech (defined according to the definition

of TechAmerica), zero otherwise. ln(Assets) is the natural logarithm of book value of assets (in millions

of U.S. dollars (converted into 2009 constant dollars using the GDP deflator)). NWC/Assets is the

difference between working capital (Compustat item WCAP) and cash and short-term investments

divided by book value of assets. Industry sigma is the mean of the standard deviations of cash flow

(operating income before depreciation (Compustat item OIBDP) – interest and related expense

(Compustat item XINT) – income taxes (Compustat item TXT)) to book value of assets ratio over 10

years (if there are at least three observations) for firms in the same industry, as defined by the two-digit

SIC code. HHI is Herfindahl-Hirschman Index and is calculated using sales data of individual firms in

the same industry, as defined by the four-digit SIC code. FCF/Assets is free cash flow (operating

income before depreciation – interest and related expense – income taxes – common stock dividends

(Compustat item DVC)) to book value of assets ratio. Book-to-market is book value of assets divided

by market value of assets. CAPEX /Assets is capital expenditures (Compustat item CAPX) to book

value of assets ratio. R&D/Assets is research and development expense (Compustat item XRD) divided

by book value of assets. R&D dummy is equal to one when R&D expense is unreported in Compustat

and zero otherwise. Book leverage is debt (the sum of long-term debt (Compustat item DLTT) and debt

in current liabilities (Compustat item DLC)) over book value of assets. Payout ratio is a sum of

common stock dividends and absolute value of the difference between purchase of common and

preferred stock (Compustat item PRSTKC) and preferred stock redemption value (Compustat item

PSTKRV) divided by market value of equity (common shares outstanding * closing share price at the

end of the fiscal year). Dividend dummy is equal to one if common stock dividends are positive and

zero otherwise. Debt issuance/Assets is the difference between long-term debt issuance (Compustat

item DLTIS) and long-term debt reduction (Compustat item DLTR) divided by book value of assets.

Equity issuance/Assets is the difference between sale of common and preferred stock (Compustat item

SSTK) and purchase of common and preferred stock divided by book value of assets.

Acquisitions/Assets is acquisitions (Compustat item AQC) divided by book value of assets. p-values

based on standard errors robust to clustering by firm are reported in parentheses.

45

Table VII (continued)

Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7

Dependant variable Market cash

ratiot

Book cash

ratiot

Market cash

ratiot

Book cash

ratiot

Market cash

ratiot+1

Book cash

ratiot+1

Market cash

ratiot

Top5 holdingst 0.043 0.089 0.042 0.086 0.032 0.077 0.042

(0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000)

High-tech dummyt 0.024 0.021 0.024 0.021 0.022 0.017 0.023

(0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000)

ln(Assets)t –0.009 –0.011 –0.009 –0.011 –0.008 –0.010 –0.009

(0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000)

NWC/Assetst –0.071 –0.109 –0.071 –0.110 –0.062 –0.101 –0.070

(0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000)

Industry sigmat 0.002 0.004 0.002 0.004 0.002 0.004 0.002

(0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000)

HHIt

–0.018

(0.000)

FCF/Assetst 0.006 0.031 0.006 0.031 0.013 0.014 0.006

(0.005) (0.000) (0.008) (0.000) (0.000) (0.001) (0.007)

Book-to-market ratiot 0.119 –0.045 0.119 –0.044 0.079 –0.044 0.119

(0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000)

CAPEX/Assetst –0.183 –0.403 –0.184 –0.407 –0.196 –0.370 –0.186

(0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000)

R&D/Assetst 0.114 0.330 0.114 0.330 0.105 0.409 0.112

(0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000)

R&D dummyt –0.014 –0.019 –0.014 –0.019 –0.011 –0.015 –0.014

(0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000)

Book leveraget –0.116 –0.181 –0.115 –0.180 –0.111 –0.166 –0.115

(0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000)

Payout ratiot

–0.025 –0.066

(0.002) (0.000)

Dividend dummyt –0.010 –0.025 –0.010 –0.024 –0.014 –0.026 –0.010

(0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000)

Debt issuance/Assetst 0.065 0.153 0.065 0.153 0.053 0.105 0.065

(0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000)

Equity issuance/Assetst 0.041 0.219 0.041 0.218 0.028 0.090 0.041

(0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000)

Acquisitions/Assetst –0.117 –0.292 –0.117 –0.293 –0.126 –0.253 –0.116

(0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000)

Year fixed effects Yes Yes Yes Yes Yes Yes Yes

R2 0.255 0.343 0.255 0.344 0.177 0.295 0.256

Adjusted R2 0.255 0.343 0.255 0.344 0.177 0.295 0.256

Number of observations 117,928 117,928 117,861 117,861 105,140 105,149 117,928

46

Table VIII

Determinants of Firm Value

This table presents the results of least squares regressions where the dependent variable is firm value

proxied by Tobin’s q. Q is Tobin’s q (market value of assets (book value of assets (Compustat item AT)

– common equity (Compustat item CEQ) + common shares outstanding (Compustat item CSHO) *

closing share price at the end of the fiscal year (Compustat item PRCC_F)) divided by book value of

assets). Top5 holdings is the ownership controlled by five largest institutional investors. We assume that

firms not covered by Thomson Reuters have no institutional investors. High-tech dummy equals one if

a firm is from high-tech (defined according to the definition of TechAmerica), zero otherwise.

ln(Assets) is the natural logarithm of book value of assets (in millions of U.S. dollars (converted into

2009 constant dollars using the GDP deflator)). Book leverage is debt (the sum of long-term debt

(Compustat item DLTT) and debt in current liabilities (Compustat item DLC)) over book value of

assets. Book cash ratio is cash and short-term investments (Compustat item CHE) divided by book

value of assets. EBIT/Assets is earnings before interests and taxes (the sum of income before

extraordinary items (Compustat item IB), interest and related expense (Compustat item XINT), and

income taxes (Compustat item TXT)) divided by book value of assets. PPE/Assets is net property,

plant, and equipment (Compustat item PPENT) divided by book value of assets. CAPEX /Assets is

capital expenditures (Compustat item CAPX) to book value of assets ratio. Dividend dummy is equal to

one if common stock dividends (Compustat item DVC) are positive and zero otherwise. Payout ratio is

a sum of common stock dividends and absolute value of the difference between purchase of common

and preferred stock (Compustat item PRSTKC) and preferred stock redemption value (Compustat item

PSTKRV) divided by market value of equity (common shares outstanding * closing share price at the

end of the fiscal year). p-values based on standard errors robust to clustering by firm are reported in

parentheses.

47

Table VIII (continued)

Model 1 Model 2 Model 3 Model 4 Model 5 Model 6

Dependant variable Qt Qt+1 Qt+1 Qt Qt Qt+1

Qt 0.534

(0.000)

Top5 holdingst 0.263 0.177 0.055 0.246 0.642 0.446

(0.001) (0.030) (0.208) (0.003) (0.000) (0.000)

High-tech dummyt 0.147 0.157 0.078 0.052 0.155 0.163

(0.000) (0.000) (0.000) (0.135) (0.000) (0.000)

ln(Assets)t –0.220 –0.214 –0.103 –0.148 –0.220 –0.213

(0.000) (0.000) (0.000) (0.000) (0.000) (0.000)

Book leveraget 1.755 1.647 0.788 1.726 1.760 1.651

(0.000) (0.000) (0.000) (0.000) (0.000) (0.000)

Book cash ratiot* Top5 holdingst –2.157 –1.551

(0.000) (0.000)

Book cash ratiot 2.842 2.384 0.861 2.624 3.085 2.554

(0.000) (0.000) (0.000) (0.000) (0.000) (0.000)

EBIT/Assetst –2.299 –2.240 –0.937 –2.401 –2.293 –2.235

(0.000) (0.000) (0.000) (0.000) (0.000) (0.000)

PPE/Assetst –1.213 –0.816 –0.148 –1.046 –1.211 –0.815

(0.000) (0.000) (0.000) (0.000) (0.000) (0.000)

CAPEX/Assetst 4.590 2.207 –0.261 3.990 4.573 2.195

(0.000) (0.000) (0.033) (0.000) (0.000) (0.000)

Dividend dummyt 0.672 0.598 0.266 0.660 0.589

(0.000) (0.000) (0.000) (0.000) (0.000)

Payout ratiot –2.505

(0.000)

Year fixed effects Yes Yes Yes Yes Yes Yes

R2 0.404 0.353 0.540 0.407 0.4043 0.3533

Adjusted R2 0.404 0.353 0.540 0.406 0.4042 0.3531

Number of observations 141,693 126,499 126,492 132,220 141,693 126,499

48

Table IX

Sensitivity Analysis

This table presents the sensitivity analysis. Using the coefficient estimates of Model 6 from Table VIII, we calculate hypothetical lead values

of Tobin’s q using different values of Top5 holdings and Book cash ratio, and mean values of other variables. Then we calculate the

difference between the computed numbers and the hypothetical lead value of Tobin’s q that is computed using mean values of all variables

including Top5 holdings and Book cash ratio. The mean values of Book cash ratio and Top5 holdings as well as the corresponding effects on

firm value are in bold style. The last column (Diff.) shows the impact on firm value than Book cash ratio increases from 0.000 to 0.400.

Book cash ratio

0.000 0.025 0.050 0.075 0.100 0.125 0.150 0.175 0.200 0.225 0.250 0.275 0.300 0.325 0.350 0.375 0.400 Diff.

To

p5

ho

ldin

gs

0.000 –0.47 –0.40 –0.34 –0.28 –0.21 –0.15 –0.08 –0.02 0.04 0.11 0.17 0.23 0.30 0.36 0.43 0.49 0.55 1.02

0.025 –0.46 –0.39 –0.33 –0.27 –0.21 –0.14 –0.08 –0.02 0.05 0.11 0.17 0.24 0.30 0.36 0.42 0.49 0.55 1.01

0.050 –0.45 –0.38 –0.32 –0.26 –0.20 –0.14 –0.07 –0.01 0.05 0.11 0.17 0.24 0.30 0.36 0.42 0.48 0.55 0.99

0.075 –0.43 –0.37 –0.31 –0.25 –0.19 –0.13 –0.07 –0.01 0.05 0.11 0.18 0.24 0.30 0.36 0.42 0.48 0.54 0.98

0.100 –0.42 –0.36 –0.30 –0.24 –0.18 –0.12 –0.06 0.00 0.06 0.12 0.18 0.24 0.30 0.36 0.42 0.48 0.54 0.96

0.116 –0.42 –0.36 –0.30 –0.24 –0.18 –0.12 –0.06 0.00 0.06 0.12 0.18 0.24 0.30 0.36 0.42 0.47 0.53 0.95

0.125 –0.41 –0.35 –0.29 –0.24 –0.18 –0.12 –0.06 0.00 0.06 0.12 0.18 0.24 0.30 0.36 0.41 0.47 0.53 0.94

0.150 –0.40 –0.34 –0.28 –0.23 –0.17 –0.11 –0.05 0.01 0.06 0.12 0.18 0.24 0.30 0.35 0.41 0.47 0.53 0.93

0.175 –0.39 –0.33 –0.28 –0.22 –0.16 –0.10 –0.05 0.01 0.07 0.12 0.18 0.24 0.30 0.35 0.41 0.47 0.52 0.91

0.200 –0.38 –0.32 –0.27 –0.21 –0.15 –0.10 –0.04 0.01 0.07 0.13 0.18 0.24 0.29 0.35 0.41 0.46 0.52 0.90

0.225 –0.37 –0.31 –0.26 –0.20 –0.15 –0.09 –0.04 0.02 0.07 0.13 0.18 0.24 0.29 0.35 0.40 0.46 0.51 0.88

0.250 –0.36 –0.30 –0.25 –0.19 –0.14 –0.09 –0.03 0.02 0.08 0.13 0.19 0.24 0.29 0.35 0.40 0.46 0.51 0.87

0.275 –0.35 –0.29 –0.24 –0.19 –0.13 –0.08 –0.03 0.03 0.08 0.13 0.19 0.24 0.29 0.35 0.40 0.45 0.51 0.85

0.300 –0.33 –0.28 –0.23 –0.18 –0.13 –0.07 –0.02 0.03 0.08 0.14 0.19 0.24 0.29 0.35 0.40 0.45 0.50 0.84

0.325 –0.32 –0.27 –0.22 –0.17 –0.12 –0.07 –0.02 0.04 0.09 0.14 0.19 0.24 0.29 0.34 0.39 0.45 0.50 0.82

0.350 –0.31 –0.26 –0.21 –0.16 –0.11 –0.06 –0.01 0.04 0.09 0.14 0.19 0.24 0.29 0.34 0.39 0.44 0.49 0.80

0.375 –0.30 –0.25 –0.20 –0.15 –0.10 –0.05 0.00 0.04 0.09 0.14 0.19 0.24 0.29 0.34 0.39 0.44 0.49 0.79

0.400 –0.29 –0.24 –0.19 –0.14 –0.10 –0.05 0.00 0.05 0.10 0.15 0.19 0.24 0.29 0.34 0.39 0.44 0.48 0.77

0.425 –0.28 –0.23 –0.18 –0.14 –0.09 –0.04 0.01 0.05 0.10 0.15 0.20 0.24 0.29 0.34 0.39 0.43 0.48 0.76

0.450 –0.27 –0.22 –0.17 –0.13 –0.08 –0.03 0.01 0.06 0.10 0.15 0.20 0.24 0.29 0.34 0.38 0.43 0.48 0.74

0.475 –0.26 –0.21 –0.16 –0.12 –0.07 –0.03 0.02 0.06 0.11 0.15 0.20 0.24 0.29 0.33 0.38 0.43 0.47 0.73

49

Table X

Simultaneous Equation Model

This table presents the results of three-stage least squares regression where the dependent variables are

book leverage, payout ratio, and book cash ratio. Book leverage is debt (the sum of long-term debt

(Compustat item DLTT) and debt in current liabilities (Compustat item DLC)) over book value of

assets (Compustat item AT). Payout ratio is a sum of common stock dividends (Compustat item DVC)

and absolute value of the difference between purchase of common and preferred stock (Compustat item

PRSTKC) and preferred stock redemption value (Compustat item PSTKRV) divided by market value

of equity (common shares outstanding (Compustat item CSHO) * closing share price at the end of the

fiscal year (Compustat item PRCC_F)). Book cash ratio is cash and short-term investments (Compustat

item CHE) divided by book value of assets. Top5 holdings is the ownership controlled by five largest

institutional investors. We assume that firms not covered by Thomson Reuters have no institutional

investors. High-tech dummy equals one if a firm is from high-tech (defined according to the definition

of TechAmerica), zero otherwise. ln(Assets) is the natural logarithm of book value of assets (in millions

of U.S. dollars (converted into 2009 constant dollars using the GDP deflator)). NWC/Assets is the

difference between working capital (Compustat item WCAP) and cash and short-term investments

divided by book value of assets. Industry sigma is the mean of the standard deviations of cash flow

(operating income before depreciation (Compustat item OIBDP) – interest and related expense

(Compustat item XINT) – income taxes (Compustat item TXT)) to book value of assets ratio over 10

years (if there are at least three observations) for firms in the same industry, as defined by the two-digit

SIC code. HHI is Herfindahl-Hirschman Index and is calculated using sales data of individual firms in

the same industry, as defined by the four-digit SIC code. FCF/Assets is free cash flow (operating

income before depreciation – interest and related expense – income taxes – common stock dividends)

to book value of assets ratio. Book-to-market is book value of assets divided by market value of assets.

Assets growth is the annual growth rate of book value of assets. EBIT/Assets is earnings before interests

and taxes (the sum of income before extraordinary items (Compustat item IB), interest and related

expense, and income taxes) divided by book value of assets. PPE/Assets is net property, plant, and

equipment (Compustat item PPENT) divided by book value of assets. R&D/Assets is research and

development expense (Compustat item XRD) divided by book value of assets. R&D dummy is equal to

one when R&D expense is unreported in Compustat and zero otherwise. CAPEX /Assets is capital

expenditures (Compustat item CAPX) to book value of assets ratio. Dividend dummy is equal to one if

common stock dividends are positive and zero otherwise. Debt issuance/Assets is the difference

between long-term debt issuance (Compustat item DLTIS) – long-term debt reduction (Compustat item

DLTR) divided by book value of assets. Equity issuance/Assets is the difference between sale of

common and preferred stock (Compustat item SSTK) and purchase of common and preferred stock

divided by book value of assets. Acquisitions/Assets is acquisitions (Compustat item AQC) divided by

book value of assets. p-values are reported in parentheses.

50

Table X (continued)

Dependant variable Book leveraget Payout ratiot Book cash ratiot

Book leveraget 0.042 –0.122

(0.000) (0.000)

Payout ratiot –0.565

(0.000)

Top5 holdingst –0.201 –0.051 0.010

(0.000) (0.000) (0.115)

High-tech dummyt –0.006 –0.003 0.015

(0.020) (0.000) (0.000)

Ln(Assets)t –0.003 0.005 –0.014

(0.000) (0.000) (0.000)

NWC/Assetst 0.019

(0.000)

Industry sigmat 0.004

(0.000)

HHIt –0.066

(0.000)

FCF/Assetst 0.071

(0.000)

Book-to-market ratiot –0.099 0.015 –0.040

(0.000) (0.000) (0.000)

Assets growtht –0.025

(0.000)

EBIT/Assetst –0.299 0.002

(0.000) (0.131)

PPE/Assetst 0.398

(0.000)

R&D/Assetst –0.302 0.462

(0.000) (0.000)

R&D dummyt 0.045 –0.001

(0.000) (0.487)

CAPEX/Assetst –0.059

(0.000)

Dividend dummyt 0.005

(0.000)

Debt issuance/Assetst –0.123

(0.000)

Equity issuance/Assetst 0.249

(0.000)

Acquisitions/Assetst –0.300

(0.000)

Year fixed effects Yes

System weighted R2 0.197

Number of observations 108,129