Insiders_Feb 09

Ronald Masulis and Shawn Mobbs
Vanderbilt University & The University of Alabama

Governance reforms emphasize outside directors
◦ Sarbanes-Oxley, Exchange Listings, Institutional Investors
◦ Pressured firms to decrease insider representation

Little research on the role of inside directors
◦ Extensive board structure research- focuses on outside directors

Two opposing theories of the role of inside directors
◦ Evidence of greater CEO influence
◦ Valuable contributors of firm-specific information
 Fama and Jensen (1983), Harris and Raviv (2008), Raheja (2005)
 Coles et al. (2008), Klein (1998)

Can we distinguish between the two?

Outside directors differ in degrees of independence

External labor market for directorships

Inside directors’ differ in degrees of independence

Are independent inside directors (IIDs) valuable board
members?
◦ Mace (1971), Hallock (1997), Core et al (1999), Shivdasani and Yermack
(1999), Hermalin and Weisbach (2003)
◦ Valuable decision management and control skills: Fama and Jensen
(1983), Brickley, Linck and Coles (1999), Kaplan and Reishsus (1990)
 Independent Inside Directors – hold outside directorships
 Indicates valuable decision management and control skills
 Greater career opportunities apart from their current CEO
Agency Perspective: Inside directors aid CEO entrenchment and
extraction of private benefits of control
H1
Inside directors with outside directorships (independent inside
directors), are predicted to be more common in firms with less
powerful or less entrenched CEOs.
H2
Boards with independent inside directors are better informed
and have stronger more talented inside directors. Thus, these
firms should have better firm performance and stock valuation.
Optimal Board Perspective: Advisory roles of inside directors enhance
board decision making, which is especially important when major
decisions must be made.
H3
Non-CEO inside directors are predicted to be more common and to
enhance firm value when Information Importance is high; specifically in
firms with one or more of the following attributes (1) high growth
opportunities, (2) a large, complex organizational structure and (3)
highly competitive product markets. Independent inside directors are
predicted to be especially valuable and frequent due to their greater
independence and market recognition of their superior skills.
H4
Inside directors are more valuable and more frequent when outside
directors have substantial board power, such as when (1) the chairman
of the board is not the CEO or (2) the board includes a large majority of
independent outside directors, since there is a greater need for firmspecific knowledge in either case. Independent inside directors should
be especially frequent and lead to greater firm performance in such
firms.

IRRC Data ~ S&P 1500 firms; 1997-2003 (Panel Data)

Exclude
◦ Finance and Utility Firms
◦ Firms where CEO≥64 years old; Hermalin and Weisbach
(1988)

Final Sample:
◦ Director observations
 6,371 non-CEO inside directors
 11% are IIDs
 Firms: 1,987
 9% have one or more IIDs

Firm Characteristics – Boone et al. (2007), Linck et al. (2008),
Coles et al. (2008), Denis and Sarin (1999)
◦ Size, R&D, Capital Expenditures, Leverage, Business & Geographic
Segments
◦ Past Performance, M&A

CEO Influence
◦ Tenure, Age, Ownership, Founder or Relative is active in firm

SOX Influence

Methodology: Multivariate OLS, Tobit and Logit regressions
◦ Industry fixed effects
◦ Robust standard errors clustered by firm
Information Importance
R&D/Assets+++
Capital Expenditure/Sales++
Ln(Sales)
+++
+++
Leverage
Ln(# of Business Segments)
Ln(# of Geographic Segments)+
%
Non-Independent
Insiders
%
Independent
Insiders
Model 1
OLS
Model 2
OLS
-6.97**
1.41*
(0.018)
(0.075)
-0.08***
0.017***
(0)
(0.004)
-0.59***
0.423***
(0)
(0)
-2.63**
-0.45
(0.031)
(0.147)
-0.319
-0.037
(0.254)
(0.67)
-0.11
0.263**
(0.756)
Industry Competition
0.0001
(0.695)
CEO Characteristics
Ln(CEO Tenure)+++
CEO Percent Ownership
+++
Board Ownership% +++
Founder Present
+++
Founder Family Present
(0.013)
-0.0002**
(0.014)
1.26***
0.32***
(0)
(0)
0.23***
-0.01
(0)
(0.196)
0.12***
-0.0002
(0)
(0.963)
3.52***
0.21
(0)
(0.2)
0.67
0.13
(0.4)
(0.548)
Firm Performance & Activity
continued…
Table 3. Determinants of Inside Directors
% Non-Independent % Independent
Insiders
Insiders
(0.4)
(0.548)2
Model
Model 1
Firm Performance & Activity
Volatility
Operating CF(t-1)
Recent M&A
Post-SOX+++
Number of Observations
Adjusted(Psuedo)-R2
1.99
-0.4
(0.543)
(0.54)
0.01***
0.00003
(0)
(0.977)
0.55*
0.35***
(0.08)
(0.001)
-2.16***
-0.5***
(0)
(0.001)
7082
20.64%
7082
7.22%

There are differences among inside directors

Independent inside directors are more likely where
theory predicts insiders to bring the most value

Decision to have non-CEO inside directors is not random
o Heckman (1979) – Self-Selection Model
 1st stage – Probit model (Table 3 Model 3)
 Compute Inverse Mills Ratio
 Identification and IV - SOX indicator (exogenous shock)
 2nd stage – Regression of performance measure
 Firms with inside directors
 Inverse Mills Ratio – control for private information
 Industry fixed effects, robust standard errors

Controls follow Coles et al. (2006), Anderson and Reeb
(2003), Fich and Shivdasani (2006)
o Firm Size, Business Segments, Firm Age
o CEO & Board Ownership, Presence of Founder or Family member
o Growth Opportunities, Return Volatility
Table 4. Firm Performance Regressions

Firm Performance Measures
 Industry Adjusted Operating Performance (CF)
 Industry Adjusted Ln(M/B)
Independent Insiders
CF
Model 1
0.0013***
ln(M/B)
Model 2
0.005***
CF
Model 3
0.0013***
ln(M/B)
Model 4
0.0067***
(0.002)
(0.005)
(0.005)
(0.001)
-0.00004
0.002**
(0.848)
(0.023)
Dependent Insiders
.
.
Controls
Inverse Mills Ratio .
Number of Observations
Censored
Firms with Inside Directors
Prob > c2
-0.123
-.127***
(0)
6302
(0.163)
3002
3300
0.00
3002
3310
0.00
6312
-.127***
(0)
-0.107
(0.225)
6302
3002
3300
0.00
6312
3002
3310
0.00
Table 5. Performance Regressions & Undiscovered
Independent Inside Directors
% Undiscovered Independent Insiders
CF
Model 1
0.002***
DCF
Model 2
Dln(MtB)
Model 4
(0.363)
(0.005)
Inside director acquires a directorship
ln(M/B)
Model 3
0.003
0.00812
0.062*
(0.577)
(0.083)

Outside directorships are a signal of talented executives

Acquiring an outside directorships is associated with
improved M/B – less agency costs (more CEO independence)
Greater CEO influence (tenure, ownership, duality) may
hinder IIDs association with performance.
Underperforming firms may get more independent directors
due to increased shareholder pressure.
Table 7. Performance Regressions: Firms with highly
entrenched CEOs
Explanatory Variables
Independent Insiders X High CEO Entrenchment
Independent Insiders X Low CEO Entrenchment
CF
Model 1
0.001
ln(M/B)
Model 2
0.0033
CF
Model 3
0.0008
ln(M/B)
Model 4
0.0054**
(0.176)
(0.154)
(0.201)
(0.04)
0.003***
0.008***
(0)
(0.006)
Dependent Insiders X High CEO Entrenchment
Dependent Insiders X Low CEO Entrenchment
High CEO Entrenchment
0.0026*** 0.0084***
(0)
(0.006)
0.00003
0.0021*
(0.92)
(0.074)
-0.0002
0.0009
(0.445)
(0.454)
-0.011**
0.004
-0.015*
-0.019
(0.024)
(0.825)
(0.063)
(0.566)

IIDs have a stronger association with firm performance
and value when the CEO is less entrenched

Non-IIDs may be an alternative means for CEOs to
entrench themselves

Growth Opportunities
 R&D, Capital Expenditures, High Tech Industry

Complex firms
 Size, Business Segments, Geographic Reach, Firm Age

Competition

Board composition
 Greater outside representation
 Separate CEO and Chair
Table 8A. High R&D Activity
Explanatory Variables
Independent Insiders X High R&D
Independent Insiders X Low R&D
CF
Model 1
0.005***
ln(M/B)
Model 2
0.011***
CF
Model 3
0.005***
ln(M/B)
Model 4
0.014***
(0)
(0.001)
(0)
(0)
0.0002
0.005**
0.0001
0.006***
(0.704)
(0.01)
(0.86)
(0.001)
0.001**
0.007***
(0.016)
(0)
-0.0002
0.001*
(0.27)
(0.09)
Dependent Insiders X High R&D
Dependent Insiders X Low R&D




Differences are significant at 1% level
Differences are significant at 5% level
Differences are significant at 1% level
Strongest effect is in High R&D

Table 8B. Performance & Organizational
Complexity
Principal Component Analysis
◦
◦
◦
◦

Firm size
Business segments
Geographic reach
Firm age
Organizational Complexity Factor Score
Explanatory Variables
Independent Insiders X High Complexity
Independent Insiders X Low Complexity
CF
Model 1
0.0011**
ln(M/B)
Model 2
0.0074***
CF
Model 3
0.0009
ln(M/B)
Model 4
0.007**
(0.044)
(0.002)
(0.152)
(0.01)
0.0016**
0.00089
0.0017**
0.0041
(0.023)
(0.756)
(0.022)
(0.172)
-0.0003
-0.001
(0.385)
(0.656)
0.0001
0.004***
(0.705)
(0)
Dependent Insiders X High Complexity
Dependent Insiders X Low Complexity
High Complexity
-0.004
-0.031
0.0015
0.03968
(0.405)
(0.14)
(0.858)
(0.233)
Explanatory Variables
Independent Insiders X High Competition
Independent Insiders X Low Competition
CF
Model 1
0.002***
ln(M/B)
Model 2
0.0102***
CF
Model 3
0.002**
ln(M/B)
Model 4
0.0108***
(0)
(0)
(0.011)
(0)
0.0004
0.0018
0.0005
0.004
(0.478)
(0.445)
(0.436)
(0.113)
-0.001*
0.001
(0.073)
(0.472)
0.000065
0.0026**
(0.811)
(0.015)
Dependent Insiders X High Competition
Dependent Insiders X Low Competition
High Competition
-0.002
-0.076*
0.008
-0.052
(0.799)
(0.052)
(0.475)
(0.274)
When survival is most critical, independent inside
directors are most valuable!

“…unless boards are given better access to information,
simply increasing board [outside] independence is not
sufficient to improve governance.”
Adams and Ferreira (2007)
Table 9. Performance Regressions & Board
Monitoring Mechanisms
Explanatory Variables
Independent Inside Directors
60% Independent Outsiders
Separate CEO and Chair
Independent Inside Directors
X Separate CEO and Chair
Independent Inside Directors
X 60% Independent Outsiders
60% Independent Outsiders
X Separate CEO and Chair


CF
Model 1
0.0013***
CF
Model 2
0.0009*
CF
Model 3
0.0007
ln(M/B)
Model 4
0.005***
(0.002)
(0.069)
(0.263)
(0.006)
0.00652*
0.0066*
0.00674
0.006
(0.096)
(0.093)
(0.207)
(0.714)
-0.0004
-0.003
-0.002
-0.007
(0.923)
(0.529)
(0.736)
(0.682)
0.0017*
0.0018*
(0.082)
(0.074)
ln(M/B)
Model 5
0.003
(0.116)
ln(M/B)
Model 6
0.003
(0.314)
0.006
(0.705)
0.005
(0.812)
-0.017
(0.36)
0.007*
(0.088)
-0.015
(0.503)
0.007*
(0.083)
0.001
(0.735)
-0.003
(0.923)
0.00035
(0.679)
-0.002
(0.786)
Greater outside representation alone may not be sufficient!
Independent inside directors appear more important than
independent outside directors!
Table 14. CARs: Announcements of Outside
Directorship Appointments

Event Study
 Direct test of shareholder wealth impact
 Directorship appointments must be to unaffiliated firms
 3-day CAR based on a one factor market model

Panel A:
 98 Announcements of Independent appointments
 Mean CAR:
1.07%** Median CAR:
.6%***


Panel A: Valuable Independent Inside directors
Examine Departures
 123 Announcements
 CARs
 Mean: -1.1%***
 Median: -.6%*

Sub-samples





No Successor mentioned
Retirement departure
Leaving for another firm
Post SOX
-1%
-.8%
-2.6%
-1.5%
Panel B: Dependent Inside Director Departures
 No significant effect, but generally positive in sign

Alternative IID measure: IID indicator

Outlier Adjustments
 Median regressions
 Winsorize data at 1% and 99% levels

Endogeneity





Self-Selection of inside directors (undiscovered IIDs)
Treatment model (non-CEO inside directors)
2SLS IV regressions (IVs: SOX Indicator and CEO tenure)
Firm Fixed Effects
Qualitative results are invariant!

Non-CEO Inside directors are heterogeneous and
independent insiders can often increase firm value

Outside directorships is one important mechanism for
distinguishing inside directors who are more valuable to the
board and shareholders

Taking into account differences among inside directors and
among firms can be important in:
◦ Future research on corporate boards
◦ Policy/governance reforms

Inside directors are valuable to information intensive firms

IIDs are more valuable than non-IIDs

Independent inside directors can be as important as
“independent” outside directors!

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