tobin's q, managerial ownership, and analyst coverage

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Tobin’s Q, Managerial Ownership, and

Analyst Coverage

A Nonlinear Simultaneous Equations Model

Carl R. Chen and Thomas L. Steiner

This paper estimates a simultaneous equations model with analyst coverage, managerial

ownership and firm valuation jointly determined within the system. We argue that both

managerial ownership (serving an internal monitoring function) and analyst coverage

(serving an external monitoring function) enhance firm value, while managerial ownership

and analyst coverage are substitutes in the monitoring of the firm. The empirical results

based upon a nonlinear three-stage-least-square procedure lead to several interesting

conclusions: First, we find a diminishing substitution effect between managerial owner-

ship and analyst coverage and a decreasing marginal value for managerial ownership.Second, we find support for both an alignment effect and an entrenchment effect in the

relationship between managerial ownership and Tobin’s Q after controlling for the effect

of analyst coverage. Third, we find support for the argument that analyst coverage serves

to enhance firm valuation after controlling for the effect of managerial ownership. Finally,

we find that analyst coverage, managerial ownership and firm valuation are jointly

determined. © 2000 Elsevier Science Inc.

Keywords: Firm value; Managerial ownership; Analyst coverage

JEL classification: G30; G32

I. Introduction

This paper studies the joint determination of firm valuation, managerial ownership and

analyst coverage. Specifically, we argue that both internal monitoring (managerial own-

ership) and external monitoring (analyst coverage) enhance firm value, although we find

that firm value is retarded when managerial ownership exceeds 28.8%. We also postulate

Professor of Finance, University of Dayton, Dayton, OH (CRC and TLS).Address correspondence to: Carl R. Chen, Department of Finance, University of Dayton, 300 College Park,

Dayton, OH 45469-2251

Journal of Economics and Business 2000; 52:365–382 0148-6195 / 00 / $–see front matter© 2000 Elsevier Science Inc., New York, New York PII S0148-6195(00)00024-2



that higher firm value inspires higher managerial ownership, and invites more analyst

coverage. Yet, while we argue that both managerial ownership and analyst coverage

increase firm value, we contend that they are substitutes for one another in monitoring the

firm.1

Firm Value and Monitoring

Jensen and Meckling (1976) make persuasive arguments that predicts managerial own-

ership serves to align the interests of managers and outside equityholders such that a

positive relationship is expected between managerial ownership and firm valuation. Stulz

(1988) develops a model of firm valuation in which entrenchment effects result in a

negative relationship between managerial ownership and firm valuation at a sufficiently

high level of managerial ownership. Furthermore, Jensen and Meckling argue analyst

coverage to be a positive determinant of firm valuation. They state: “We would expect

monitoring activities to become specialized to those institutions and individuals who

possess comparative advantages in these activities. One of the groups who seem to playa large role in these activities is composed of the security analysts . . . .”2 They further

argue that if “. . . security analysis activities reduce the agency costs associated with the

separation of ownership and control they are indeed socially productive. Moreover, if this

is true we expect the major benefits of security analysis activity to be reflected in the

higher capitalized value of the ownership claims to corporations.”3 4

Several empirical studies have used Tobin’s Q as a measure of valuation to study the

relationship between managerial ownership and firm valuation. These papers include

Morck, Shleifer, and Vishny (1988) and McConnell and Servaes (1990) that offer support

for both the positive alignment effect and the negative entrenchment effect. The empirical

models, however, do not account for the monitoring effects associated with analystcoverage. Chung and Jo (1996) fill this gap in the literature by empirically testing the

relationship between the number of analysts and Tobin’s Q and find a positive relation-

ship. Their study, however, does not model the effect associated with the percentage of

managerial ownership. As a consequence of the incompleteness of these existing studies,

it remains a vital issue as to the relationships between managerial ownership and firm

valuation and between analysts coverage and firm valuation after each effect is properly

controlled within the same model.

Joint DeterminationIn an effort to formulate a proper empirical model of these relationships, we argue that

analyst coverage, managerial ownership and Tobin’s Q are jointly determined and,

therefore, should be modeled within a three-equation system of equations. An argument

1 We use the terms “analyst coverage” and “number of analysts” interchangeably in the paper.2 Jensen, M. and W. Meckling. 1976. Theory of the firm: managerial behavior, agency costs and ownership

structure. Journal of Financial Economics 3:354.3 Jensen, M. and W. Meckling. 1976. Theory of the firm: managerial behavior, agency costs and ownership

structure. Journal of Financial Economics 3:355.4 Similar causal arguments can be inferred based upon the research of Merton (1987) who argues for a

positive relation between the level of awareness by investors (investor cognizance) of a stock and its valuation.To the extent a higher number of analysts increase this investor cognizance, the number of analysts are expectedto positively cause the level of firm valuation.

366 C. R. Chen and T. L. Steiner



for this empirical specification can be supported from a closer examination of earlier

empirical research while this examination also allows us to gain additional insights into

the relationships between these variables.

Chung and Jo (1996) jointly model Tobin’s Q and analyst coverage using a simulta-

neous equation estimation procedure. They argue that the amount of analyst coverage is

a determinant of Tobin’s Q and Tobin’s Q is a determinant of the amount of analystcoverage. Their empirical results are supportive of this joint dependency. Moyer, Chat-

field, and Sisneros (1989) also model the amount of analyst coverage using a single

equation estimation procedure; they find this measure to be negatively impacted by the

percentage of insider ownership. This finding suggests the possibility that the Chung and

Jo model should be expanded to include managerial ownership as an endogenous variable.

Two points are relevant:

1. Moyer, Chatfield, and Sisneros contend that the relationship between managerial

ownership and the number of analysts is consistent with a substitution effect which

they infer from the arguments of Jensen and Meckling (1976). Their empiricalmodel, however, assumes a linear substitution effect. This linear effect, in turn,

implicitly assumes a constant marginal value for managerial ownership that is

inconsistent with, for example, the observed entrenchment effects in the Tobin’s Q

literature [McConnell and Servaes (1990)]. If the marginal value of managerial

ownership diminishes, we may expect the causal inverse relationship from mana-

gerial ownership to analyst coverage to diminish.

2. The substitution effect argument made by Moyer, Chatfield, and Sisneros could

similarly be applied to a causal relationship from analyst coverage to managerial

ownership. Indeed, it is possible that their results are spurious if they capture a

relationship by which analyst coverage is a determinant of managerial ownershiprather than their hypothesized relationship by which managerial ownership is a

determinant of analyst coverage. This counter argument is plausible because analyst

coverage mitigates the value of managerial ownership as an internal monitoring

force. As a final point, the determinants of managerial ownership have been

investigated by Crutchley and Hansen (1989) and Jensen, Solberg, and Zorn (1992),

yet these two studies have not explored the possible effect of analyst coverage on

managerial ownership.

Research Issues and ImplicationsThe consequence of these prior theoretical arguments of Jensen and Meckling (1976) and

Stulz (1988) together with the empirical results of Morck, Shleifer, and Vishny (1988),

Moyer, Chatfield, and Sisneros (1989), Crutchley and Hansen (1989), McConnell and

Servaes (1990), Jensen, Solberg, and Zorn (1992), and Chung and Jo (1996) make a case

for the possibility that analyst coverage, managerial ownership and firm valuation are

jointly determined. This endogeneity argument might be more simply represented by

Figure 1 in which selected theoretical and empirical research which are supportive of the

relationships between the three endogenous variables are presented. The solid lines in the

figure represent causal relationships found in the existing literature that can be reexamined

within our proposed system of equations. The dotted lines represent causal relationshipsnot previously examined in the existing literature, but hypothesized to be true by the

current research. Therefore, our research objective in this paper is to expand this area of

Tobin’s Q, Managerial Ownership, and Analyst Coverage 367



the financial literature that has investigated the interactions among alternative monitoring

agents and among monitoring agents and firm valuation. Our research design allows us to

more carefully examine the following questions:

● What is the relationship between managerial ownership and firm valuation after

controlling for the effect of analyst coverage? What is the relationship betweenanalyst coverage and firm valuation after controlling for the effect of managerial

ownership?

● What is the causal relationship between managerial ownership and analyst coverage?

Is managerial ownership a determinant of analyst coverage? Is analyst coverage a

determinant of managerial ownership? Are these two monitoring functions substitute

or complement?

● Are firm valuation, managerial ownership, and analyst coverage jointly determined?

From the results of our empirical analysis, we offer a number of interesting conclu-

sions:

1. The level of managerial ownership is a nonlinear determinant of firm valuation and

analyst coverage is a positive determinant of firm valuation. At low levels of

Figure 1. The relationships between Tobin’s Q, managerial ownership and analyst coverage




managerial ownership the relationship between managerial ownership and Tobin’s

Q is positive in support of an alignment effect; at high levels of managerial

ownership the relationship is negative in support of an entrenchment effect. The

findings are consistent with the arguments of Jensen and Meckling (1976) and Stulz

(1988), and shed light on the empirical research of Morck, Shliefer and Vishny

(1988), McConnell and Servaes (1990), and Chung, and Jo (1996) after both analystcoverage and managerial ownership effects are included within the same model of

valuation.

2. The percentage of managerial ownership is a nonlinear determinant of the number

of equity analysts. We argue the result is explained by a diminishing substitution

effect and a diminishing marginal value for managerial ownership that becomes

negative at a sufficiently high percentage of managerial ownership. The explanation

of this relationship runs parallel to the explanation for the causal relationship from

managerial ownership to Tobin’s Q. Furthermore, the inflection point in the rela-

tionship between managerial ownership and analyst coverage is impressively close

to the inflection point in the relationship between managerial ownership and Tobin’sQ. This result serves to extend the empirical research of Moyer, Chatfield, and

Sisneros (1989) and Chung and Jo (1996) by offering more insight into the

interaction between internal and external monitoring forces.

3. Analyst coverage is a negative determinant of managerial ownership. This result is

consistent with a substitution effect and a diminishing marginal value to external

monitoring in the form of analyst coverage. The result serves to extend the empirical

research of Crutchley and Hansen (1989) and Jensen, Solberg, and Zorn (1992),

which do not consider the impact of analyst coverage on managerial ownership.

4. Analyst coverage, managerial ownership and firm valuation are jointly determined.

5. Our conclusions are robust to the inclusion of institutional ownership effects and toalternative methods for measuring the financial variables.

The remainder of the paper is structured as follows: in Section II, the data, method-

ology, and testable hypotheses are presented; in Section III, the empirical results are

reviewed; concluding remarks are made in Section IV.

II. Data, Methodology, and Testable Hypotheses

Data and Models

We study a sample of firms as of December 1994. The sample of firms used in the studyincludes all NYSE and AMEX firms which have relevant financial data on Compustat,

CRSP, Analyst Concensus Estimates (ACE), and Compact Disclosure databases. The total

number of firms meeting these data requirements is 824. The following abbreviations are

used to represent the variables employed in the study:

Q Tobin’s Q;

NANL Number of analysts making earnings estimates for a particular firm;

LNANL Log of the number of analysts;

OWN Percentage of managerial ownership defined to be the shares owned by

officers and directors (as reported in the firm’s proxy statement and thecompact disclosure data base) divided by the total shares outstanding.

OWN 2 Percentage of managerial ownership squared;




LTA Log of the total firm value measured as the book value of total assets;

LEQTY Log of the equity value measured as the stock price times the shares

outstanding;

DA Total debt divided by total assets;

DISP Dispersion of the analyst’s consensus growth estimates as measured by the

standard deviation of the estimates; RDA Research and development expense divided by the total assets in the firm;

ROA Net Income divided by the total assets in the firm;

GRTH Analysts’ consensus growth rate forecast;

1/ P The inverse of the stock price per share;

SD Total risk of the firm’s equity measured as the standard deviation of the

market returns;

NYSE 1 if the firm is listed on the New York Stock Exchange, 0 otherwise.

INST The percentage of institutional ownership5

We develop a simultaneous-equation model with analyst coverage, managerial own-ership, and Tobin’s Q jointly determined within the model.6 The three-equation model can

be represented as:

LNANL ƒ (OWN, OWN2, Q, LEQTY, RDA, GRTH, SD, NYSE, 1/P),7 (1 )

OWN ƒ (LANL, Q, LEQTY, DA, RDA, SD, DIV), (2)

Q ƒ(OWN, OWN2, LANL, LTA, DA, DISP, RDA, ROA). (3)

The variables included in the models consider prior research and model identification.

Analyst Coverage Equation

Managerial ownership (OWN) is included to capture the substitution effect between

internal and external monitoring. Moyer, Chatfield, and Sisneros (1989) consider this

relationship using a linear specification. However, our model includes the square of

managerial ownership (OWN2) to capture the possibility of a diminishing substitution

effect and the possibility of a turning point in the relationship consistent with a decreasing

value for managerial ownership (McConnell and Servaes (1990)). Tobin’s Q is included

based upon Chung and Jo’s (1996) argument that Q is a measure of the quality of the firm

and higher quality firms are easier to market.

The exogenous variables included are: size (LEQTY), stock price (1/P), risk (SD),growth potential (GRTH), research and development (RDA), and New York Stock

Exchange listing (NYSE).8 LEQTY is expected to be a significant, positive determinant

5 We later include institutional ownership into the model as an examination of the robustness of the results.6 The use of a simultaneous equations methodology has a been employed by a number of previous studies

in finance. See, for example: Bathala, Moon, and Rao (1994), Jensen, Solberg, and Zorn (1992), Jalilvand andHarris (1984), Peterson and Benesh (1983), McCabe (1979), and Dhrymes and Kurz (1967).

7 We assume a log-liner functional form for variable NANL (number of analysts). Since most economicvariables exhibit diminishing marginal returns, we conjecture that a diminishing monitoring effect is reasonableif the marginal contribution to monitoring by analysts decreases as their numbers increase (also see Chung andJo, 1996 for similar arguments). We also assume a log-liner functional form for variables EQTY and TA as theyare the most popular one for these two variables found in many prior studies.

8 The exogenous variables are the same as those employed by Chung and Jo (1996).




of LNANL. Presumably a large equity value will be associated with a higher trading

volume that justifies the cost of the additional information acquired by the analysts.

Brennan and Hughes (1991) develop a theoretical model with empirical support for an

inverse relationship between the share price and analyst following. They argue that stock

splits reduce the relative share price and at the same time stock splits signal a brighter

future for the firm which attracts more analysts. Bhushan (1989) contends that risk increases the value of the analyst’s supply of information. Research and development

(RDA) is included to capture the possibility that R&D intensive firms are more likely to

be followed by more analysts because they are perceived as higher quality firms. Chung

and Jo (1996) offer arguments supportive of this reasoning. On the other hand, high RDA

firms may diminish the need for external monitoring in the form of analyst coverage

consistent with the free cash flow hypothesis of Jensen (1986). More specifically, if

research and development serves to lower the level of free cash flow, and therefore agency

problems associated with free cash flow, then the value of analyst coverage as an external

monitoring force may be reduced yielding a lower level of analyst coverage. Chung and

Jo (1996) similarly contend that NYSE listed firms are better known firms and perceivedas being higher quality firms, therefore these firms are more likely to receive more analyst

coverage. Finally, Moyer, Chatfield, and Sisneros (1989) report a positive relationship

between firm growth (GRTH) and analyst coverage. They argue that high growth firms

require the additional monitoring from more analysts.

Managerial Ownership Equation

We postulate that analyst coverage determines the percentage of managerial ownership.

Consistent with the arguments of Jensen and Meckling (1976), who contend that both

managerial ownership and analyst coverage serve as monitoring forces in the firm, weargue that a higher level of external monitoring in the form of analyst coverage will reduce

the need for internal monitoring provided by managerial ownership. Moreover, we expect

the magnitude of this substitution effect to decrease as the number of analysts increase.

This is expected if the marginal value of an additional analyst diminishes and, conse-

quently, the substitution effect is retarded. Tobin’s Q is also included as a determinant of

managerial ownership. We anticipate that higher quality firms, as measured by a higher

Tobin’s Q, will inspire higher percentages of managerial ownership. Consistent with the

self-interest of managers, we would expect a manager’s decision to commit financial

capital, as well as human capital, to a firm to be a function of the quality of the firm. The

exogenous variables in this equation include size (LEQTY), debt (DA), research anddevelopment (RDA), risk (SD), and dividend policy (DIV). Each variable has been used

in previous research to model managerial ownership.9

9 Although not exactly the same as managerial ownership, Demsetz (1983) and Demsetz and Lehn (1985)make persuasive arguments regarding the determinants of the ownership concentration. They argue that theopportunity for shirking should encourage the formation of a more concentrated ownership structure. However,as the firm size increases, increasing percentages of wealth are needed to achieve the same percentageownership; therefore, as the size of the firm increases the concentration should fall. They also argue that firmswhich operate in risky markets are more difficult to monitor externally; as such, the higher the risk, the greaterthe need for a concentrated ownership, and the higher the level of concentration. However, they also contend thatat sufficiently high levels of risk, a negative relation between risk and ownership concentration may result dueto risk aversion. Consistent with their arguments, Demsetz and Lehn (1985) report empirically that size isnegatively related and risk is nonlinearly related to ownership concentration.




Crutchley and Hansen (1989) use the direct ownership by officers and directors as

reported by Spectrum to measure managerial ownership. They find that this measure is

positively related to risk (SD), negatively related to size (LEQTY), and inversely, but not

significantly, related to research and development expense (RDA). Jensen, Solberg, and

Zorn (1992) find insider ownership, as reported by Value Line, to be negatively related to

size (LEQTY) while they also argue that insider ownership is a function of the amount of dividends (DIV) and the level of debt (DA). Size is expected to negatively impact

managerial ownership because wealth constraints prevent managers from obtaining a large

percentage of equity as the firm size increases. Debt is also expected to be a negative

determinant of managerial ownership because higher debt firms are more intensively

exposed to the monitoring process of the market. Demsetz and Lehn (1985) contend that

a firm’s control potential is directly associated with the noisiness of the environment in

which it operates. Their arguments suggest a more risky firm may require a higher level

of managerial ownership or inside monitoring due to asymmetric information. Further-

more, the higher the level of research and development expense and the higher the

dividend, the lower the firm’s free cash flow and, thus, the lower the need for managerialownership to control agency problems associated with free cash flow (Jensen, 1986).

Tobin’s Q Equation

Managerial ownership (OWN) is expected to nonlinearly impact firm valuation consistent

with the alignment and entrenchment effects of Jensen and Meckling (1976) and Stulz

(1988) and consistent with the empirical findings of Morck, Shleifer, and Vishny (1988)

and McConnell and Servaes (1990). We expect the number of analysts (LNANL) to

positively cause Q consistent with the arguments of Jensen and Meckling (1976) that

outside monitoring reduces agency costs. This is also consistent with the empirical

findings of Chung and Jo (1996). Firm size, measured by total assets (LTA), research and

development expense (RDA), profitability (ROA), the dispersion of analysts’ forecasts

(DISP) and analyst coverage (LNANL) were found to be significant determinants of

Tobin’s Q in Chung and Jo (1996). A negative relation between LTA and Q may be

expected due to the tendency for firms with higher total assets to be more diversified

which, in turn, has been found to negatively impact firm valuation (Lang and Stulz

(1994)). Both profitability (ROA) and research and development (RDA) are expected to

positively cause firm valuation. In addition to Chung and Jo (1996)., these findings are

also reported by Hirschey (1982), Cockburn and Griliches (1988), Morck, Shleifer, and

Vishny (1988), McConnell and Servaes (1990), and Hall (1993). The dispersion of

analysts’ forecasts, which serve as a proxy of ex ante risk (see Farrelly and Reichenstein,

1984), is expected to be a negative determinant of Tobin’s Q.

We estimate Equations (1–3) simultaneously using a nonlinear-three-stage-least-

squares estimation procedure. The procedure yields efficient, and unbiased parameter

estimates (Green, 1997).

Hypotheses

The simultaneous equations model allows us to test four primary hypotheses: Hypothesis 1. The number of analysts following a firm is a nonlinear function of the

percentage of managerial ownership consistent with a substitution effect. At lower levels




of managerial ownership, managerial ownership serves to align the interests of manage-

ment and outside equity holders allowing for a substitution effect between managerial

ownership and the amount of external monitoring through equity analysts. At higher levels

of managerial ownership, managerial ownership serves to entrench management which

leads to a higher level of external monitoring from equity analysts.

Hypothesis 2. The percentage of managerial ownership is an inverse function of the

number of equity analysts following a firm. This is because the number of equity analysts

serves as a substitute for managerial ownership in monitoring the firm. We contend that

agency costs are reduced if a firm has significant monitoring by equity analysts. Conse-

quently, the firm may find it less important to institute policies which motivate managerial

ownership.

Hypothesis 3. Both managerial ownership (internal monitoring) and analyst coverage

(external monitoring) reduce agency costs and thus impact firm value. The percentage of

managerial ownership is a nonlinear determinant of the valuation of the firm aftercontrolling for the level of analysts coverage. Over low levels of managerial ownership,

we expect a positive relationship between managerial ownership and valuation in support

of an alignment effect. Over higher levels of managerial ownership, we expect a negative

relationship in support of an entrenchment effect. We further expect the number of

analysts to be a significant positive determinant of firm valuation after controlling for the

percentage of managerial ownership as the monitoring effect of analysts serves to enhance

valuation.

Hypothesis 4. Analyst coverage, managerial ownership, and firm valuation are jointly

determined.

III. Empirical Results

The empirical results are reported in Tables 1 through 3. Table 1 offers simple descriptive

statistics on the variables used in the model. Table 2 reports the parameter estimates of

Equations 1–3 using the nonlinear three-stage-least-squares estimation procedure. Figures

2 and 3 allow for a graphical representation of the findings. Table 3 examines the

robustness of the results after including institutional ownership effects and after measuring

the financial variables using three year averages.

Descriptive Statistics

Table 1 shows the average number of analysts following a sample firm to be 11.63 with

a standard deviation of 7.69. The figure is slightly lower than the mean of 16.8 reported

in Chung and Jo (1996). The average percentage of managerial ownership is 9.79% with

a standard deviation of 13.63%. This is slightly higher than the 6.4% reported in Crutchley

and Hansen (1989), however, it is slightly lower than the alternative measure of insider

ownership of 13.8% reported in McConnell and Servaes (1990). The mean value of

Tobin’s Q for sample firms is 1.50 with a standard deviation of 0.77. The mean level of

Tobin’s Q in the Chung and Jo study (1996) is approximately 1.0. Our statistics deviateslightly from prior studies due to two factors. First, our sample period is in the early 1990s,

while other studies focus on the 1980s. It is intuitively clear that low inflation in




conjunction with high stock market valuation result in higher Tobin’s Q in the 1990s.

Second, variations in sample size may also explain the deviations in some statistics. For

example, our sample contains 824 observations, while Crutchley and Hanses (1989) haveapproximately 600. The mean level of total assets is $4,134 million, and the mean value

of the equity market value is $3,267 million. The mean level of the debt-to-asset ratio is

56.73%. The estimated growth in earnings for the average firm is 13.3%, with a standard

deviation of 6.8%. The dispersion of the analyst growth estimates measured by the

standard deviation of the growth estimates is 2.88%. Research and development, as a

percentage of total assets, is 1.85% with a standard deviation of 3.09%. Return on assets

has a mean level of 5.45%. The standard deviation of the market returns of a firm’s stock

is 1.84%, and the dividend yield has a mean value of 2.29% with a standard deviation of

2.42%. Finally, the NYSE dummy variable shows that 93.81% of the sample firms are

listed on the New York Stock Exchange.

Primary Results

Table 2 reports the results of the nonlinear three-stage-least-squares estimates for the

simultaneous equation model defined by Equations 1–3. The model allows us to test the

hypotheses advanced in Section II of this paper.

Equation 1 in Table 2 offers an empirical model of analyst coverage which enables us

to test Hypothesis 1. In this model we find the level of managerial ownership to be

nonlinearly related to the number of analysts in support of Hypothesis 1. The negative

value of variable OWN is consistent with a monitoring substitution effect between NANLand OWN. This substitution effect, however, is increasingly retarded at higher percentages

of managerial ownership due to the positive sign of variable OWN2. The inflection point

Table 1. Descriptive Statistic on Variables

N Mean SD Min Max

NANL 824 11.6347 7.6955 1.0000 38.00

OWN 824 9.7907 13.6272 0.0005 82.158

Q 824 1.4961 0.7668 0.0906 7.7728TA 824 4,134 12,164 34.042 198,598

LTA 824 7.1522 1.4642 3.5276 12.199

EQTY 824 3,267 7,761.75 23.796 87,004

LEQTY 824 6.9378 1.4753 3.1695 11.374

DA 824 56.7298 16.4490 2.3813 99.3588

GRTH 824 13.3003 6.8299 2.0000 74.500

DISP 824 2.8811 3.5284 0.0000 40.060

RDA 824 1.8515 3.0900 0.0000 33.884

ROA 824 5.4500 6.1485 56.7378 52.281

SD 824 1.8366 0.6545 0.7727 7.2294

DIV 824 2.2870 2.4246 0.0000 24.421

NYSE 824 0.9381 0.2411 0.0000 1.000

Notes: This table reports descriptive statistics on all variables used in the study. NANL is the number of analysts, OWN isthe percentage of managerial ownership, and Q is Tobin’s Q. TA is the firm’s total asset in $million, and LTA is the logarithmof the total assets. EQTY stands for the total market value of a firm’s equity in $million, and LEQTY is the logarithm of themarket value of equity. DA is the total debt as a percentage of total assets. GRTH is the forecasted long-term analysts’ concensusgrowth rate. DISP is the dispersion of the analysts’ consensus growth estimates. RDA is research and development as apercentage of the total assets in the firm. ROA is the return on assets. SD is the standard deviation of the market returns of afirm’s stock. DIV is the dividend yield, and NYSE is a dummy variable that takes a value of one if the firm’s stock is tradedover the NYSE, zero otherwise.




in the relationship is at 27.68%.10 The interpretation of this inflection point may be that

as the percentage of managerial ownership increases, the marginal value of managerial

ownership diminishes thus causing the substitution monitoring effect between the per-

centage of managerial ownership and the number of analysts to be retarded. Indeed, for a

level of managerial ownership above 27.68%, the marginal value of managerial ownership

is no longer positive which increases the value of analyst monitoring. This yields a

positive causal relationship between the percentage of managerial ownership and the

10 The inflection point is calculated as the derivative of analyst coverage with respect to managerialownership. A similar inflection point is calculated for the relationships between Tobin’s Q and managerialownership.

Table 2. A Nonlinear 3SLS Model of Tobin’s Q, OWN, and LNANL

LNANL OWN Q

Intercept 1.0118 31.4998 1.4015

(6.53)*** (7.95)*** (3.18)***

LNANL — 3.7085 1.1038(2.93)*** (9.07)***

OWN 0.0609 — 0.1903

(4.05)*** — (6.13)***

OWN2 0.0011 — 0.0033

(3.03)*** — (4.67)***

Q 0.0737 2.6655 —

(2.24)** (3.09)*** —

LEQTY 0.4421 2.0712 —

(30.09)*** (5.57)*** —

LTA — — 0.0870

— — (2.70)***

DISP — — 0.0087— — (0.89)

ROA — — 0.0433

— — (7.18)***

DA — 0.0127 0.0024

— (0.41) (1.00)

RDA 0.0111 0.3818 0.0324

(1.77)* (2.64)*** (2.56)***

1/P 1.4278 — —

(3.57)*** — —

GRTH 0.0043 — —

(1.33) — —

SD 0.1498 0.3825 —(4.48)*** (0.47) —

DIV — 0.8592 —

— (3.45)*** —

System R2 55.60% 55.60% 55.60%

Notes: This table reports nonlinear three-stage-least-squares models of a three equation system with Q, OWN, and NANL jointly determined within the model. Q is Tobin’s Q, LNANL is the log of the number of analysts. OWN is the percentage of managerial ownership, and OWN2 is the square of OWN. LEQTY is the logarithm of the market value of equity. LTA is thelogarithm of total assets. DISP is the dispersion of analysts earnings forecast. ROA is the return on assets. RDA is research anddevelopment as a percentage of the total assets in the firm. DA is the total debt as a percentage of the assets. 1/P is the inverseof stock price. GRTH is the forecasted long-term analysts’ consensus growth rate. SD is the standard deviation of market returns.DIV is the dividend yield. We control for NYSE listing in the LNANL equation, but for ease of presentation we do not reportthis insignificant parameter estimate. We use data from 1994. ***, **, and * indicate significance at the 1%, 5% and 10% level

of confidence.




number of analysts. Interestingly, this is also consistent with the empirical relationship

between managerial ownership and Tobin’s Q where we find the marginal value of managerial ownership above 28.83% (the inflection point) to be negative. This empirical

result is interesting because it shows how both monitoring forces interact and how they

serve to impact firm valuation. The result is supportive of Hypothesis 1.

We also find the level of Tobin’s Q to positively impact analyst coverage in Equation

1. These results are consistent with the arguments advanced by Chung and Jo (1996), that

analysts find it easier to market firms which are more highly regarded by the market. The

exogenous variables in Equation 1 include equity value (LEQTY), research and devel-

opment (RDA), growth (GRTH), inverse of the stock price (1/P), and risk (SD). Consis-

tent with Moyer, Chatfield, and Sisneros (1989), the market value of equity (LEQTY)

which often is used as a proxy of firm size, carries a positive and significant parameterestimate. Both the inverse of the stock price and the risk measure are positive and

significant at the 1% level of confidence as expected. The negative parameter of RDA,

This figure presents graphical representations of the relationships between managerial ownership and analystcoverage. The graphs are developed based upon the estimated models in Table 2. Control variables are heldconstant at their mean values in order to present the functions in this figure.

Figure 2. Graphical representations of the relationships between OWN and NANL




however, is supportive of the free cash flow argument. Growth potential, although

positive, is not statistically significant.In Equation 2, the percentage of managerial ownership is modeled within the system

of equations which enables us to test Hypothesis 2. In this equation, analyst coverage is

inversely related to the percentage of managerial ownership consistent with the discus-

sions of a substitution effect and Hypothesis 2 set forth in the prior section of the paper.

The employment of the log of the number of analysts yields a diminishing substitution

effect as the number of analysts increases. This diminishing effect is reasonable if the

marginal contribution to monitoring by analysts decreases as their numbers increase.

Tobin’s Q is a positive and significant determinant of managerial ownership. This is

consistent with self-interested managers committing higher levels of financial capital to a

high quality firm. The exogenous variables in this equation include market value of equity(LEQTY), debt (DA), research and development (RDA), risk (SD), and the dividend yield

(DIV). The LEQTY has a strong inverse relationship to the percentage of managerial

This table presents graphical representations of the relationships between Tobin’s Q and managerial ownershipand between Tobin’s Q and analyst coverage. The graphs are developed based upon the estimated models inTable 2. Control variables are held constant at their mean values in order to present the functions in this figure.

Figure 3. Graphical representations of the relationships between Tobin’s Q and OWN and betweenTobin’s Q and NANL




ownership, and the financial leverage measure (DA) is inversely related to the percentage

of managerial ownership although the relationship is not statistically significant. The level

of research and development (RDA) and the dividend yield (DIV) are both inversely and

significantly related to the percentage of managerial ownership consistent with the free

cash flow argument. The risk variable (SD) carries a positive sign, but is statistically

insignificant.

Equation 3 studies the determinants of Tobin’s Q. In support of Hypothesis 3, thepercentage of managerial ownership is a nonlinear function of the firm value as measured

by Tobin’s Q. The nonlinear function estimates an inflection point at 28.83%. This can be

Table 3. A Nonlinear 3SLS Model of Tobin’s Q, OWN, and LNANL With InstitutionalOwnership Effects and Using Averaged Financial Data

LNANL OWN Q

Intercept 1.2471 22.2461 0.3562

(7.07)*** (5.67)*** (1.33)LNANL — 5.3055 0.6167

— (4.17)*** (7.21)***

OWN 0.0708 — 0.0853

(5.04)*** — (4.99)***

OWN2 0.0013 — 0.0011

(3.89)*** — (2.88)***

Q 0.0846 4.5867 —

(2.20)** (5.33)*** —

INST 0.0051 — —

(5.24)*** — —

LEQTY 0.4365 1.2732 —

(28.90)*** (3.48)*** —LTA — — 0.0510

— — (2.64)***

DISP — — 0.0040

— — (0.64)

ROA — — 0.0707

— — (14.95)***

DA — 0.0238 0.0014

— (0.75) (0.88)

RDA 0.0102 0.4244 0.0377

(1.71)* (3.24)*** (5.66)***

1/P 2.4569 — —

(3.62)*** — —GRTH 0.0100 — —

(2.82)*** — —

SD 0.1148 1.3807 —

(2.88)*** (1.77)* —

DIV — 0.7037 —

— (2.66)*** —

System R2 53.02% 53.02% 53.02%

Notes: This table reports nonlinear three-stage-least-squares models of a three equation system with Q, OWN, and NANL jointly determined within the model. Q is Tobin’s Q, LNANL is the log of the number of analysts. OWN is the percentage of managerial ownership, and OWN2 is the square of OWN. INST is the institutional ownership. LEQTY is the logarithm of themarket value of equity. LTA is the logarithm of total assets. DISP is the dispersion of analysts earnings forecast. ROA is thereturn on assets. RDA is research and development as a percentage of the total assets in the firm. DA is the total debt as apercentage of the assets. 1/P is the inverse of stock price. GRTH is the forecasted long-term analysts’ consensus growth rate.SD is the standard deviation of market returns. DIV is the dividend yield. We control for NYSE listing in the LNANL equation,but for ease of presentation we do not report this insignificant parameter estimate. We use averages over the years 1994, 1993,and 1992 to form the financial variables. ***, **, and * indicate significance at the 1%, 5% and 10% level of confidence.




interpreted to support the alignment effect (a positive relationship) for a level of mana-

gerial ownership below 28.83% and interpreted to support the entrenchment effect (a

negative relationship) for a level of managerial ownership above 28.83%. This is close to

the inflection point in the causal relationship from managerial ownership to analyst

coverage (Equation 1). This result is obtained after the number of analysts has been

controlled.Additionally, we find that the number of analysts is a significant and positive deter-

minant of Tobin’s Q after controlling for the effects of managerial ownership. The results

extend those offered by McConnell and Servaes (1990) into a simultaneous equation

model with an analyst effect. The model of Tobin’s Q also includes several exogenous

variables. These variables closely resemble the model offered by Chung and Jo (1996)

although their model does not include effects associated with managerial ownership. We

find the measure of firm size (LTA) to be inversely related to the firm’s valuation. This

is consistent with larger firms having a more diversified asset composition which, in turn,

has been shown to retard market valuations (Lang and Stulz, 1994). Both RDA and ROA

carry positive parameter estimates and are highly significant which is consistent withmany prior findings in the Tobin’s Q literature. The debt to asset ratio (DA) and the

dispersion of analysts’ earnings forecast (DISP), however, are not statistically significant.

Overall, the results from estimating the simultaneous equations model defined by

Equations 1–3 yield a number of interesting conclusions. First, in support of Hypothesis

1 and Hypothesis 2, we find managerial ownership and analyst coverage to be jointly

dependent and inversely related. As additional clarification of these relationships, Figure

2 offers a graphical representation of the joint dependency between managerial ownership

and analyst coverage. The presentation in Figure 2 is based upon the models estimated in

Table 2 with control variables held constant at their mean values. Second, consistent with

Hypothesis 3, we find support for both the alignment and the entrenchment effect aftercontrolling for the monitoring performed by equity analysts, and we find the number of

analysts to positively impact the firm valuation after controlling for the percentage of

managerial ownership. Figure 3 offers a graphical representation of these relationships.

The presentation in Figure 3 is based upon the models estimated in Table 2 with control

variables held constant at their mean values. Third, consistent with Hypothesis 4, we find

analyst coverage, managerial ownership, and firm valuation to be jointly determined.

Additional Results

In this section, we further examine the endogenous relationships between Tobin’s Q,

managerial ownership, and analyst coverage. We examine the robustness of the findingsafter we control for the effects of institutional ownership and after we measure the

financial variables as averages over a three-year period from 1992 through 1994.

The motivation for examining the institutional ownership effect is provided by Bat-

thala, Moon, and Rao (1994) and by O’Brien and Bhushan (1990). Batthala, Moon, and

Rao use institutional ownership as an exogenous variable in examining a simultaneous

equation model with managerial ownership and debt as endogenous variables. They

identify an inverse relationship between institutional ownership and debt, but did not find

such a relationship between institutional ownership and managerial ownership for NYSE

and AMEX firms.11 O’Brien and Bhushan (1990) examine a model in which analyst

11 Our data are limited to firm traded in the NYSE and AMEX.




coverage and institutional ownership are assumed to be endogenous. After controlling for

the simultaneity effect between the changes in the analyst coverage and the changes in the

institutional ownership using a two-stage-least-square method, they did not find the

analyst coverage (institutional ownership) to impact institutional ownership (analyst

coverage). In light of O’Brien and Bhushan’s finding, we propose that institutional

holdings influence analyst coverage, which, in turn, impacts firm value.12 We report theresults in Table 3. We find that institutional ownership has a significant and positive effect

on the level of analyst coverage. Additionally, our overall model remains robust to the

inclusion of this variable.

As a final examination of the robustness of our model, we measure the financial

variables as averages over a three-year period of time. This is motivated by previous

researchers such as Jensen, Solberg, and Zorn (1992) who have used this approach. Table

3 offers the results from using this approach. The results are reported with the institutional

ownership effects included. The conclusions we have reached in this paper are not

sensitive to this change in the measurement of the variables. More specifically, we again

find strong support for an endogenous relationship between Tobin’s Q, managerialownership, and analyst coverage.

VI. Conclusions

This paper offers a nonlinear simultaneous-equations model of analyst coverage, mana-

gerial ownership and firm valuation. The treatment of these measures as jointly deter-

mined is motivated from earlier theoretical and empirical research. Overall, we find that

after controlling for the effect of exogenous variables in the system, both internal

monitoring (measured by managerial ownership) and external monitoring (measured byanalyst coverage) enhance firm value (measured by Tobin’s Q) although firm value is

retarded when the managerial ownership exceeds 28.8%. Furthermore, the negative

relationship between analyst coverage and managerial ownership suggests the existence of

a substitution effect between these two monitoring forces. More specifically, this paper

offers several interesting results: First, we find a nonlinear causal relationship from

managerial ownership to the number of equity analysts. The relationship supports a

diminishing substitution effect and a decreasing marginal value for managerial ownership.

We find the inflection point of 27.68% in this relationship to be interestingly close to the

inflection point of 28.83% in the causal relationship from managerial ownership to

Tobin’s Q. Second, we find an inverse, causal relationship from the number of equityanalysts to the percentage of managerial ownership. Third, we find the relationship

between managerial ownership and Tobin’s Q to be nonlinear after controlling for the

influence of analyst coverage, and we find the relationship between analyst coverage and

Tobin’s Q to be positive and significant after controlling for the percentage of managerial

ownership. Finally, we find analyst coverage, managerial ownership, and firm valuation

to be jointly determined in a simultaneous equation system.

We acknowledge the beneficial comments of two anonymous referees in addition to the effort of Robert Taggartand Kenneth Kopecky, the editors.




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