Does Corporate Governance Really Matter?

Does Corporate Governance Really Matter?





David F. Larcker

Scott A. Richardson

rem Tuna



The Wharton School
University of Pennsylvania
Philadelphia, PA 19104-6365






June 9, 2004






We would like to thank David Chun and Roger Boissonnas of Equilar Inc. and J. Thomas
Quinn of TrueCourse Inc. for their considerable help on this research project.

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Does Corporate Governance Really Matter?

Abstract


We examine the relation between a broad set of corporate governance factors and various
measures of managerial behavior and organizational performance. Using a sample of
2,126 firms we distill 38 structural measures of corporate governance (e.g., board
characteristics, stock ownership, anti-takeover variables etc.) to 13 governance factors
using principal components analysis. For a wide set of dependent variables (e.g.,
abnormal accruals, excessive CEO compensation, debt ratings, analyst recommendations,
Q and over-investment) we find that the 13 governance factors on average explain only
1% to 5.5% of the cross-sectional variation using standard OLS multiple regression
techniques and 1.4% to 9.1% of the variation using exploratory recursive partitioning
techniques. Overall, our results suggest that the typical structural indicators of corporate
governance used in academic research and institutional rating services have very limited
ability to explain managerial behavior and organizational performance.

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Does Corporate Governance Really Matter?
1. Introduction

Corporate governance generally refers to the set of mechanisms that influence the
decisions made by managers when there is a separation of ownership and control. Some
of these monitoring mechanisms are the board of directors, institutional shareholders, and
operation of the market for corporate control. The importance of this topic is obvious
from an examination of the considerable growth in the empirical literature on corporate
governance across accounting, economics, finance, management, and corporate strategy
literatures.1 Typical research studies examine whether different corporate governance
structures impact or constrain executive behavior and/or have an impact on
organizational performance. Examples of these types of studies are Morck, Shleifer, and
Vishny (1988), Byrd and Hickman (1992), Brickley, Coles and Terry (1994), Yermack
(1996), Core, Holthausen, and Larcker (1999), Klein (2002), Gompers, Ishii, and Metrick
(2003).2

Although prior work has provided some insight into the role of corporate
governance, the results of similar studies are frequently contradictory and a consistent set
of results has yet to emerge regarding the importance of corporate governance for
understanding managerial behavior and organizational performance. There are at least

1 There are also many organizations that sell governance ratings (e.g., GovernanceMetrics International,
Institutional Shareholder Services, Investor Responsibility Center, and Standard & Poors). The growth in
this type of service offerings attests to the perceived importance of corporate governance issues. Although
the precise computation of these ratings is proprietary, the scores seem to be based on board independence,
distribution of ownership, and other structural characteristics. Despite considerable claims by these
organizations, we are not aware of rigorous evidence regarding the ability of these ratings to predict
managerial behavior or organizational performance (with the possible exception of Gompers, Ishii, and
Metrick, 2003; but note the discussion in Cremers and Nair, 2003 regarding the sensitivity of the Gompers,
Ishii and Metrick results).
2 Reviews of the extensive literature corporate governance literature have been provided by Shleifer and
Vishny (1997), Bhagat and Black (2002) and Bushman and Smith (2001).

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seven features of prior research that make it difficult to draw substantive conclusions.
First, most studies use a small set of convenient (easy to collect) set of indicators for
corporate governance, as opposed to developing a more comprehensive set of governance
variables. Second, each study tends to use a different set of governance variables which
makes integration across studies extremely difficult. Third, there is very little analysis
regarding the measurement properties for the selected indicators of corporate governance
(e.g., the traditional psychometric properties of reliability and construct validity).
Moreover, we do not have detailed insight into the number of dimensions (or constructs)
that are necessary to provide a comprehensive assessment of corporate governance.
Fourth, single indicators are used as measures for ill-defined and complex corporate
governance constructs (e.g., percentage of external board members). Such single
indicators are likely to have substantial measurement error for the construct of interest
(e.g., board independence) which will bias the estimated coefficients in typical
methodological approaches. Fifth, the sample size and specific firms included in the
sample vary considerably across studies depending on the dependent variable examined
and the source of the governance variables. These differences make it problematic to
compare results across studies. Sixth, most studies focus on the statistical significance, as
opposed to the incremental explanatory power, of the governance indicators. While
statistical significance is necessary, it is also important to demonstrate explanatory power
in order to draw substantive conclusions about corporate governance. Finally, the
methodological approach used is typically restricted to some type of linear model where
complex interactions among governance are not considered. Since empirical governance

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research is at an early stage in its evolution, it would be useful to use more exploratory
methods as a complement to traditional linear model approaches.

The purpose of this paper is to develop new measures for corporate governance
from a comprehensive set of indicators and then apply these new measures to a large
sample of firms and across a wide range of dependent variables. We pay particular
attention to developing governance indices that mitigate measurement error and provide a
parsimonious structure for our tests. The results of our principal component analysis
indicates that 13 factors characterize the dimensionality of 38 individual governance
indicators considered in our analysis (e.g., board size, directors that are members of other
boards or busy, multiple dimensions of anti-takeover devices, etc.). Although 13 factors
is a complex outcome, this might be expected, because corporate governance is a
complicated, multidimensional construct.

The 13 constructs derived from the principal component analysis are then used to
determine the importance of corporate governance for accrual choices, analyst equity
recommendations, chief executive officer (CEO) compensation, debt ratings, Tobin’s Q,
and corporate over-investment. These managerial decisions and external valuations
provide a much more comprehensive assessment for the substantive importance of
corporate governance than prior research. Moreover, since we examine multiple
dependent variables using the same set of governance constructs and the same set of
firms, this should enable us to determine whether similar governance constructs are
important across different settings.

Using both traditional multiple regression and exploratory recursive partitioning,
we find that our corporate governance constructs have limited explanatory power for

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explaining managerial choices or firm valuation. The incremental explanatory power
ranges from 1% to 5.5% for traditional multiple regression and 1.4% to 9.1% for
recursive partitioning analyses. Moreover, the signs of the estimated coefficient are
frequently unexpected. For example, in our analysis of corporate debt ratings and non-
directional measures of abnormal accruals, we find that firms with large boards, busy
directors and anti-takeover provisions (i.e., “bad governance”) tend to have better debt
ratings and lower abnormal accruals. Our overall conclusion is that the typical structural
indicators of corporate governance used in academic research and institutional rating
services have a very limited ability to explain managerial decisions and firm valuation.
These negative results imply either that corporate governance is of modest importance, or
the available indicators of corporate governance are not especially useful.

The remainder of the paper is divided into five sections. Section 2 describes the
sample selection and the governance indicators used in the study. Section 3 presents the
principal component analysis of the governance indicators and develops our 13 construct
measures for corporate governance. Section 4 describes the methodological approach
used to assess the importance of corporate governance for explaining managerial decision
making and firm valuation. The results for each dependent variable are presented in
Section 5. Section 6 provides the summary and conclusions.

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2. Sample Selection and Corporate Governance Indicators
2.1 Sample

Our sample was generated from the overlap between two comprehensive data sets.
The first data set consisted of the companies covered during 2002 and 2003 by
www.SharkRepellent.net which is a product offering by TrueCourse, Inc. that provides
data on anti-takeover provisions (n = 3,651). The anti-takeover data covers only U.S.
incorporated companies that are included in the major indices (e.g., Fortune 500, S&P
Super 1500, etc.), amended their poison pill since 2001, and/or completed a firmly
underwritten IPO since 1999. The second data set consists of companies covered by
Equilar, Inc. whose fiscal year ends between June, 2002 and May, 2003 and having
complete data on board, board committees (audit and compensation), and equity
ownership by executives and board members (n = 3,000). After merging the
SharkRepellent and Equilar data, we have a final sample of 2,126 individual firms with
complete data. Our sample spans many sectors of the economy and has a distribution of
firms that is very consistent with the composition of the complete Compustat file (see
Table 1). Our sample represents approximately 70 percent of the market capitalization of
the Russell 3000 as of the end of 2003.3
2.2 Corporate Governance Indicators

We collect indicators of corporate governance in seven general categories:
characteristics of the board of directors, stock ownership by executives and board
members, stock ownership by institutions, stock ownership by activist holders, debt and

3 Our sample only covers one year and this limits our ability to generalize the results. However, the single
year of data covers a very recent time period and prior work involving large samples also is restricted to a
single year (e.g., Bhagat, 2004 and Ashbaugh, Collins, and LaFond, 2004).

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preferred stock holdings, anti-takeover devices, and unionization. Our board of director
and executive and board ownership data is obtained from Equilar, stock ownership by
institutions and activists is collected from Spectrum data files (13F filings), debt and
preferred stock data is obtained from Compustat, anti-takeover data is collected from
SharkRepellent, and unionization (or the existence of a collective bargaining agreement)
data is collected from 10K filings.

Drawing on prior studies (e.g., Klein, 1998, Bhagat and Black, 2002, Core,
Holthausen and Larcker, 1999, and Ferris, Jagannathan and Pritchard, 2003 and others),
our board of director variables are the number of meetings for the audit committee,
compensation committee, and the total board (denoted as # AC Meetings, # CC Meetings,
and # Board Meetings, respectively), number directors serving on the compensation
committee, audit committee, and the total board (denoted as CC Size, AC Size, and Board
Size, respectively), fraction of board comprised of insider (executive) directors (denoted
as % Board Inside), fraction of the compensation committee and audit committee that is
comprised of affiliated directors (denoted as % CC Affiliated and % AC Affiliated,
respectively)4, indicator variable equal to one if the chairperson of the compensation
committee and audit committee is affiliated and zero otherwise (denoted as CC Chair
Affiliated and AC Chair Affiliated, respectively), the fraction of outside directors and
affiliated directors that serve on four or more other boards, and the fraction of inside
directors that serve on two or more boards (denoted as % Busy Outsiders, % Busy
Affiliated, and % Busy Insiders, respectively), fraction of outside, affiliated, and inside
directors that are older than 70 (denoted as % Old Outsiders, % Old Affiliated, and % Old

4 We use the definition of affiliated (or “grey”) directors developed by Equilar definition (which is a
combination of SEC, NYSE, and NASD guidelines). Any outside directors that was mentioned in the
“certain transactions” section or a former executive was classified as affiliated.

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Insiders, respectively), an indicator variable equal to one of there is a lead director (an
outside director that can call meetings of all outside directors in executive session) on the
board and zero otherwise (denoted as Lead Director), an indicator variable equal to one if
an internal executive holds the position of chairperson of the board and zero otherwise
(denoted as Insider Chairman), and the fraction of affiliated and outside directors that
were appointed by existing insiders (denoted as % Affiliated Appointed and % Outsiders
Appointed, respectively).5

Consistent with prior research (e.g., Ashbaugh, Collins, and LaFond, 2004,
Bhagat, 2004, and Klein, 1998), the typical board has about eight members with one or
two internal executives, the chairman of the board is usually an internal executive, and
there is not a lead director (see Table 2). Most of the members of the compensation and
audit committee are outsiders, but there is some evidence that the chair of these
committees is an affiliated director. In contrast to insiders, outside or affiliated directors
are generally not classified as busy. Most boards are not composed of old directors, but
a high percentage of the affiliated and outside directors were appointed by existing inside
directors.

Our board and executive ownership variables are the fraction of outstanding
shares held by the average outside director (denoted as % Outsiders Own)6, fraction of
outstanding shares held by the top executive (denoted as % Top Exec), fraction of
outstanding shares held by the average executive director after excluding the holdings of
the top executive (denoted as % Executives Own (Excl. Top)), and fraction of outstanding
shares held by the average affiliated director (denoted as % Affiliated Own). Similar to

5 This variable was measured by comparing the term of an existing board member to the maximum term for
the set of insider directors. If there were no affiliated directors, this variable was set equal to zero.
6 We exclude stock option holdings in our board and executive ownership computations.

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prior work, the median board and executive group owns less than one percent of the
outstanding equity (e.g., Hall and Liebman, 1998). However, there is considerable
skewness with these measures as evidenced by the mean being substantially larger than
the median.

Institutional ownership is measured as fraction of outstanding shares owned by
block-holders (denoted as % Block Own), number of block-holders (denoted as # Block),
and shareholding of the largest institutional owner (denoted as % Largest).7 The average
company in our sample has two block-holders that own 16 percent of the outstanding
shares (with the largest block-holder owning about nine percent of the outstanding
shares).

The activist variables are measured using the number of activist institutions
holding shares (denoted as # Activists) and the fraction of outstanding shares held by
activist institutions (denoted as % Activists Own). Activist institutions are identified
using the information contained in Cremers and Nair (2003).8 The average company in
our sample has seven activists holding a total of about two percent of the outstanding
shares.

The role of debt as a governance mechanism is measured using the ratio of book
value of debt (Compustat data item 9 plus data item 34) to the market value of equity

7 A block-holder is defined as a shareholder who holds more than five percent of outstanding shares.
8 The following public pension finds are classified as activists (Spectrum manager number): California
Public Employees Retirement System (12000), California State Teachers Retirement (12100 and 12120),
Colorado Public Employees Retirement Association (18740), Florida State Board of Administration
(38330), Illinois State Universities Retirement System (81590), Kentucky Teachers Retirement System
(49050), Maryland State Retirement and Pension System (54360), Michigan State Treasury (57500),
Montana Board of Investment (58650), Education Retirement Board New Mexico (63600), New York State
Common Retirement Fund (63850), New York State Teachers Retirement System (63895), Ohio School
Employees Retirement System (66550), Ohio School Employees Retirement System (66610), Ohio State
Teachers Retirement System (66635), Texas Teachers Retirement System (82895 and 83360), Virginia
Retirement System (90803), State of Wisconsin Investment Board (93405).

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