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 after controlling 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 deviate
slightly 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
Tobin’s Q, Managerial Ownership, and Analyst Coverage 373
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 have approximately 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 NANL and 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
7.7728 TA
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 22.0000
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 256.7378
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 is the percentage of managerial ownership, and Q is Tobin’s Q. TA is the firm’s total asset in million, and LTA is the logarithm
of the total assets. EQTY stands for the total market value of a firm’s equity in million, and LEQTY is the logarithm of the market value of equity. DA is the total debt as a percentage of total assets. GRTH is the forecasted long-term analysts’ concensus
growth rate. DISP is the dispersion of the analysts’ consensus growth estimates. RDA is research and development as a percentage of the total assets in the firm. ROA is the return on assets. SD is the standard deviation of the market returns of a
firm’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 traded over the NYSE, zero otherwise.
374 C. R. Chen and T. L. Steiner
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 managerial ownership. A similar inflection point is calculated for the relationships between Tobin’s Q and managerial
ownership.
Table 2. A Nonlinear 3SLS Model of Tobin’s Q, OWN, and LNANL
LNANL OWN
Q Intercept
21.0118 31.4998
21.4015 6.53
7.95 3.18
LNANL —
23.7085 1.1038
2.93 9.07
OWN 20.0609
— 0.1903
4.05 —
6.13 OWN2
0.0011 —
20.0033 3.03
— 4.67
Q 0.0737
2.6655 —
2.24 3.09
— LEQTY
0.4421 22.0712
— 30.09
5.57 —
LTA —
— 20.0870
— —
2.70 DISP
— —
20.0087 —
— 0.89
ROA —
— 0.0433
— —
7.18 DA
— 20.0127
20.0024 —
0.41 1.00
RDA 20.0111
20.3818 0.0324
1.77 2.64
2.56 1P
1.4278 —
— 3.57
— —
GRTH 0.0043
— —
1.33 —
— SD
0.1498 0.3825
— 4.48
0.47 —
DIV —
20.8592 —
— 3.45
— System R
2
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 the logarithm of total assets. DISP is the dispersion of analysts earnings forecast. ROA is the return on assets. RDA is research and
development as a percentage of the total assets in the firm. DA is the total debt as a percentage of the assets. 1P 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 data from 1994. , , and indicate significance at the 1, 5 and 10 level
of confidence.
Tobin’s Q, Managerial Ownership, and Analyst Coverage 375
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 1P, 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 parameter estimate. 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 analyst coverage. The graphs are developed based upon the estimated models in Table 2. Control variables are held
constant at their mean values in order to present the functions in this figure.
Figure 2. Graphical representations of the relationships between OWN and NANL 376
C. R. Chen and T. L. Steiner
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 ownership and between Tobin’s Q and analyst coverage. The graphs are developed based upon the estimated models in
Table 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 between Tobin’s Q and NANL
Tobin’s Q, Managerial Ownership, and Analyst Coverage 377
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, the percentage 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 Institutional Ownership Effects and Using Averaged Financial Data
LNANL OWN
Q Intercept
21.2471 22.2461
20.3562 7.07
5.67 1.33
LNANL —
25.3055 0.6167
— 4.17
7.21 OWN
20.0708 —
0.0853 5.04
— 4.99
OWN2 0.0013
— 20.0011
3.89 —
2.88 Q
0.0846 4.5867
— 2.20
5.33 —
INST 0.0051
— —
5.24 —
— LEQTY
0.4365 21.2732
— 28.90
3.48 —
LTA —
— 20.0510
— —
2.64 DISP
— —
20.0040 —
— 0.64
ROA —
— 0.0707
— —
14.95 DA
— 0.0238
20.0014 —
0.75 0.88
RDA 20.0102
20.4244 0.0377
1.71 3.24
5.66 1P
2.4569 —
— 3.62
— —
GRTH 0.0100
— —
2.82 —
— SD
0.1148 1.3807
— 2.88
1.77 —
DIV —
20.7037 —
— 2.66
— System R
2
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 the market value of equity. LTA is the logarithm of total assets. DISP is the dispersion of analysts earnings forecast. ROA is the
return on assets. RDA is research and development as a percentage of the total assets in the firm. DA is the total debt as a percentage of the assets. 1P 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.
378 C. R. Chen and T. L. Steiner
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 with
many 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 after
controlling 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 findings
after 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.
Tobin’s Q, Managerial Ownership, and Analyst Coverage 379
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 the results 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, managerial ownership, and analyst coverage.
VI. Conclusions
