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Monitoring the Monitor: Distracted Institutional Investors and
Board Governance*
Claire Yang Liu
UNSW Business School
UNSW Australia
Angie Low
Nanyang Business School
Nanyang Technological University
Ron Masulis
UNSW Business School
UNSW Australia
Le Zhang
UNSW Business School
UNSW Australia
This Version: May 18, 2017
* We thank Chang-Mo Kang, E. Han Kim, Bo Li, Mark Humphrey-Jenner, Ji Yeol Jimmy Oh,
Paul Karehnke, Peter Pham, David Reeb, Rik Sen, Elvira Sojli, Buvaneshwaran Venugopal, Wing
Wah Tham, and Robert Tumarkin, as well as conference participants from the FIRN Annual Conference,
Conference on Asia-Pacific Financial Markets, Australasian Finance and Banking Conference, and seminar
participants at Georgia Institute of Technology and UNSW Australia for helpful comments.
Monitoring the Monitor: Distracted Institutional Investors and Board Governance
Abstract
While boards are crucial to shareholder wealth, the literature often overlooks how
continuous shareholder oversight can improve director incentives. Using exogenous
industry shocks in investors’ portfolio firms, we find that institutional investor distraction
weakens board oversight. Distracted institutions are less likely to use their votes to
discipline ineffective independent directors, and directors with poor voting outcomes are
less likely to turnover. As a result, directors have less monitoring incentives with
independent directors missing more meetings and boards holding fewer meetings. Board
structures are also compromised with the appointment of more ineffective independent
directors and lead. to worse governance outcomes such as greater earnings management,
higher excess CEO pay, and lower firm valuation. Our findings suggest that continuous
institutional investor attention represents an important determinant of board monitoring
incentives.
Keywords: Board of directors, Shareholder activism, Institutional investors, Board
monitoring, Shareholder voting, Corporate governance.
JEL classification: G23, G34.
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1. Introduction
Large shareholders and the board of directors are two key corporate governance
mechanisms. Due to the legal and regulatory limits on the power of large shareholders in the
United States,1 the board of directors is generally considered to have a critical role in corporate
governance. The board serves as “gatekeeper” of all shareholder proposals to amend the charter
and also as the “approver” of almost all major corporate decisions. The board is also charged
with monitoring management, hiring and firing of CEOs, and setting executive compensation.
While the board is a powerful governance mechanism for monitoring managers,
director monitoring incentives do not appear to be particularly strong. This raises important
questions on how reliable are boards of directors in representing shareholder interests. What
motivates directors to monitor? Who monitors the board monitors? To address these questions,
we examine whether institutional investor monitoring on a regular basis improves board
incentives to exert greater effort in monitoring and motivating senior management.
Several recent studies report evidence that institutional investors in general improve
corporate decision making and thus, firm value.2 The existing literature tends to emphasize
shareholder actions during extreme events, e.g. proxy contests and lawsuits. However, those
actions are likely to serve as a weapon of last resort. Given the significant powers boards have
over major corporate decisions, it is more effective and less costly for shareholders to take
precautionary actions to monitor the board on a regular basis. Our study helps to further our
current understanding of director monitoring incentives, and how institutional investors
improve firm performance by continually monitoring the board.
1 In the U.S. shareholders cannot directly initiate business transactions or charter amendments, nor modify those
proposed by directors. In contrast, shareholders in the U.K., Japan, and France can force these decisions if the
proposals receive a majority vote (Hansmann and Kraakman, 2001). 2 For instance, Doidge, Dyck, Mahmudi and Virani (2015); Appel, Gormley and Keim (2016); Kempf, Manconi
and Spalt (2016); and Li, Liu, and Wu (2016).
2
Prior studies that go “behind-the-scenes” generally report evidence that institutional
investors actively intervene by engaging management and directors in active discussions.3 Less
is understood about whether such interventions result in improved director incentives and board
monitoring effectiveness. A board of directors is the only representative that shareholders have
in the firm who can make or approve major corporate decisions. Thus, the incentives of boards
to act in shareholder interests are very important in minimizing shareholder-manager agency
problems. Yet, it is unclear, whether the labour market for directors sufficiently punishes
poorly-performing directors (Fahlenbrach, Low, and Stulz, 2016).4 Furthermore, independent
directors generally have weak financial incentives to actively monitor a firm’s management on
a consistent basis (Yermack, 2004). Moreover, the existing governance literature documents
that certain types of directors are ineffective monitors. For example, independent directors who
are more socially dependent on the CEO, busy directors, non-domestic directors, co-opted
directors and possibly old directors tend to be less effective monitors.5 In the absence of
effective board monitoring, institutional investors can be exposed to severe agency problems
and experience significant losses. Thus, monitoring boards to ensure they perform their
fiduciary duties should be a critical channel through which outside investors seek to maximize
their returns on investments.
Several studies have argued that institutional investors may not actively intervene to
improve firm governance due to the classical free-rider problem as discussed in Grossman and
Hart (1980) and Shleifer and Vishny (1986). Furthermore, the threat of exit makes active
intervention less important as the potential stock price declines that result from exit may be a
3 See e.g. Becht et al. (2010); Carleton, Nelson, and Weisbach (1998); McCahery, Sautner, and Starks (2016). 4 Past literature on the directorial labor market impact of poor monitoring by directors mostly focuses on extreme
events such as earnings restatements (Srinivasan, 2005), financial fraud lawsuits (Fich and Shivdasani, 2007),
bankruptcies (Gilson, 1990), and option backdating (Ertimur, Ferri, and Maber, 2012). 5 See for example, Chidambaran, Kedia and Prabhala (2011), Coles, Daniel, and Naveen (2014), Falato,
Kadyrzhanova, and Lel (2014), Fich and Shivdasani (2006), Fracassi and Tate (2012), Hwang and Kim (2009)
(2012), Masulis and Mobbs (2014), and Nguyen (2012).
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sufficient threat to motivate managers to work hard (Kahn and Winton, 1998; Maug, 1998).
Even if institutional investors actively intervene to change firm policies, it is unclear whether
shareholder monitoring and board monitoring are close substitutes for mitigating manager-
shareholder agency conflicts. Institutional shareholders can directly monitor management and
thus, obtain direct influence over major corporate decisions, which negates the need to
otherwise intervene in board governance. Also, activist institutional investors can join the
boards to directly effect changes (Gow, Shin, and Srinivasan, 2014) without the need to
influence monitoring by other board members. Thus, it is unclear whether institutions actively
intervene to affect board governance.
We construct an exogenous measure of institutional shareholder monitoring to test
whether institutional monitoring affects board monitoring incentives. Following Kempf,
Manconi, and Spalt (2016), we address such endogeneity concerns by utilizing exogenous
variations in institutional shareholder attention, caused by unrelated industry shocks to other
portfolio firms held by the institutional investors. We use these shocks to capture reductions in
the level of institutional shareholder monitoring. The following example illustrates how such
an exogenous shock to outside monitoring of the board can occur. Suppose a mutual fund
investor has two large stockholdings belonging to two unrelated industries, for example a bank
and a pharmaceutical firm. When the pharmaceutical industry is experiencing a large return
shock, the mutual fund manager needs to allocate more time and effort to monitor the
pharmaceutical firm. Assuming the attention and effort of a fund manager is in limited supply,
we expect the bank to receive less attention. Hence, this shock reduces a mutual fund manager’s
monitoring intensity of the bank.6 To the extent that these industry-level shocks to a fund’s
6 In a similar manner, Kacperczyk, Van Nieuwerburgh, and Veldkamp (2016) model how mutual fund managers,
due to their finite mental capacity, optimally choose to allocate their limited attention to different information
depending on the business cycle. Consistent with the idea of limited resources on the part of institutional investors,
in their survey of institutional investors, McCahery, Sautner, and Starks (2016) find that limited resources
(personnel) and “too many firms in our portfolio” rank as important impediments to shareholder activism.
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portfolio firms are unrelated to the focal firm’s fundamentals, this measure captures the
exogenous variation in institutional investor monitoring intensity that is orthogonal to the focal
firm’s fundamentals.
Generalizing on the above example, we aggregate industry shocks using the weights of
the shocked industries in an institutional shareholder’s portfolio, to construct an investor-level
measure of exogenous distractions experienced by each institutional shareholder towards a
given firm in a given quarter. Next, we construct a focal firm-level investor distraction measure
by summing the distraction levels of all of its institutional investors. Kempf, Maconi, and Spalt
(2016) convincingly show that this distraction measure is negatively related to the amount of
attention institutional investors spend on monitoring a firm’s activities such as participating in
conference calls and initiating governance-related proposals.
To investigate whether investor distraction affects director incentives to monitor, we
first examine the voting behavior of institutional investors in director elections. Shareholder
voting in director elections represents one primary mechanism for institutional shareholders to
exert influence over a firm’s board and ultimately over its corporate decisions. While directors
rarely fail to be re-elected, except in proxy fights, experiencing disciplinary votes can be
embarrassing to a director and adversely affect her reputation and likelihood of being
renominated in the future (Aggarwal, Dahiya, and Prabhala, 2015). Therefore, shareholder
voting may motivate independent directors to act in shareholder interests due to these adverse
reputational impacts.
Using an investor-level measure of mutual fund distraction, we find that mutual funds
are less likely to discipline directors with negative votes when they are distracted.
Economically, a one standard deviation rise in a mutual fund investor’s distraction level is
associated with a fall in the likelihood that the investor withholds or votes against an
independent director candidate in the annual shareholder meeting by 3.3%. This effect is
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stronger for problematic director candidates, defined as those who are busy directors, directors
socially linked to the CEO, and foreign directors.7 Such directors are shown in prior studies to
be ineffective monitors.
Next, we examine how the distraction by multiple institutional investors of a firm
affects director voting outcomes. We find that independent directors in general receive
significantly fewer disciplinary votes from institutional shareholders when these investors are
distracted. Economically, one standard deviation increase in investor distraction reduces the
likelihood of an independent director receiving poor vote results by almost 5%. Consistent with
our fund vote results, this effect is stronger for problematic director candidates. In addition, the
sensitivity of director departure to poor election vote results is also significantly lower when
institutional shareholders are distracted, consistent with weaker disciplinary effects of
shareholder votes.
Taken together, the voting results indicate that independent directors, especially
problematic ones, are significantly less likely to be disciplined by voting outcomes when
institutional shareholders are distracted. Next, we examine whether weakened board oversight
by institutional shareholders affects director monitoring incentives. We find that independent
directors miss more board meetings and boards hold fewer meetings when institutional
shareholders are distracted. For example, we find that one standard deviation rise in
institutional investor distractions is associated with an almost 16% rise in the likelihood of poor
director meeting attendance. Furthermore, institutional investor distraction leads to more
problematic independent directors on the board, due to the increased likelihood of a new
7 Endogeneity issues such as unobserved heterogeneity across mutual funds, directors, and firms are unlikely to
be driving our results. As our dataset comprises of the voting outcomes of each mutual fund for individual director
elections for each firm and each year, we exploit within-investor differences in monitoring intensity across their
different portfolio firms for each year by controlling for fund-year fixed effects. We also exploit within-election
proposal differences in monitoring intensity across the mutual funds voting on each election proposal by including
individual director election proposal fixed effects, which essentially accounts for time-varying director and firm
characteristics.
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problematic director being appointed to the board and retention of existing problematic
directors. These findings suggest that the institutional investor monitoring has important
implications for director monitoring incentives and efforts.
Finally, we examine how the reduction in board monitoring efforts and incentives due
to investor distraction affects several governance outcomes. Firms with distracted investors
exhibit significantly greater earnings management, grant their CEOs higher compensation, but
with less performance-based incentives, and generally have lower equity valuation.
Importantly, the negative impact of investor distraction on these governance outcomes are
amplified in firms where problematic directors sit on key committees or where board
monitoring efforts are compromised. Taken together, our results suggest that institutional
shareholder distraction leads to significantly poorer board monitoring quality and
effectiveness.
Our study contributes to the literature on corporate governance in several ways. First,
we extend our understanding of what motivates independent directors to do their job well and
monitor management carefully. While it is well known that boards make important corporate
decisions which have economically large impacts on shareholder value, director incentives to
monitor managers are not well-understood. It is unclear why directors with limited financial
incentives are willing to exert sufficient effort to closely monitor managers (Yermack, 2004).
Fama and Jensen (1983) argue that director reputational concerns provide a strong motivation,
and recent studies show that reputational concerns affect director incentives to perform their
roles as effective monitors.8 We advance our understanding of director incentives by showing
that institutional investor oversight of boards significantly improves director incentives to exert
efforts in monitoring the senior management.
8 For instance, Jiang, Wan, and Zhao (2016); Masulis and Mobbs (2014); Levitt and Malenko (2016).
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Second, our study furthers our understanding of how institutional investors intervene
to improve board governance and firm value. Existing studies that examine shareholder
interventions in corporate governance emphasize the actions of shareholder activists during
extreme events, including the use of proxy contests and law suits.9 However, evidence on
shareholder actions to improve board functioning on a regular basis is surprisingly scarce.10
We help fill this gap in the existing literature, and show that institutional investors use their
disciplinary votes to monitor and discipline directors on a regular basis. Our study also differs
substantially from Kempf, Manconi, and Spalt (2016) who show that firms are more likely to
undertake diversifying acquisitions and grant their CEOs opportunistically-timed equity grants
when institutional investors are distracted. Given that acquisitions and CEO pay are within the
board’s decision domain, we show that the underlying mechanism through which distracted
shareholders can impact firm policies is through board monitoring and consultations. In
particular, our study highlights the important role that institutional investors play in monitoring
the board. We show that reduced institutional investor monitoring leads to poorer board
effectiveness, in part due to independent directors reducing their own monitoring efforts in
response to reduced voting pressure, and in part due to poorly chosen board appointments.
Our study is also related to the literature that explores how corporate governance
mechanisms interact with each other. Existing evidence is mixed as to how governance
mechanisms interact (Agrawal and Knoeber, 1996; Cremers and Nair, 2005; Gillan, Hartzell,
and Starks, 2011), and it remains unclear whether the monitoring roles of the board and
9 See e.g., Brav et al. (2008) on hedge fund activism, Del Guercio and Hawkins (1999) on the impact of
shareholder proposals put forward by public pension funds, Doidge et al. (2016) on the activities of Canadian
Coalition for Good Governance, a formal collective action organization of institutional investors, Del Guercio,
Seery, and Woidtke (2008) on vote-no campaigns, Gillian and Starks (2000) on detailed analysis of shareholder
proposal voting outcomes. See also Gillian and Starks (2007), Denes, Karpoff, and McWilliams (2016) for
comprehensive reviews on shareholder activism. 10 Outside shareholders can submit Rule 14a-8 shareholder proposals relating to board independence and other
board issues but they are often ineffective in eliciting change (Gillian and Starks, 2007; Denes, Karpoff, and
McWilliams, 2016). Activist shareholders can also organize “just vote no” campaigns to withhold votes from
directors but Del Guercio, Seery, and Woidtke (2008) show that such campaigns often target at large, poorly
performing firms and are typically sponsored by public pension funds.
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institutional shareholders are complements or substitutes. We contribute to this literature by
showing that the monitoring function of corporate boards, a key internal governance
mechanism, depends crucially on the effectiveness of institutional shareholder monitoring of
directors, which acts as a complementary governance mechanism.
Lastly, we contribute to the literature that examines the impact of institutional investor
monitoring on firm policies and governance outcomes. Monitoring by institutional investors is
found to have a positive impact on a firm’s governance indices, CEO compensation, mergers
and acquisitions profitability, firm risk-taking, and earnings management 11 However,
endogeneity makes it difficult to assess the causal dimension of these effects. For example,
Chung and Zhang (2011) conclude that the positive association between institutional
ownership and good governance structure is driven by institutional investors gravitating
towards firms with good governance so as to minimize their own monitoring costs. Recent
studies have used the annual reconstitution of the Russell 1000 and 2000 indexes as an
exogenous shock to examine how changes in passive institutional ownership affect firm
governance and policies.12 Our study differs from theirs in that we focus on how institutional
shareholder monitoring intensity affects board governance as a crucial internal governance
mechanism. Additionally, we examine a wide range of institutional investor classes, not just
passive index investors.
11 Examples include: Hartzell and Starks (2003), Aggarwal et al. (2011), Chen, Harford, and Li (2007), Cornett,
Marcus, Tehranian (2008), Aghion, Van Reenen, and Zingales (2013), and Kim and Lu (2011). 12 Appel, Gormley, and Keim (2016) find that an increase in passive institutional ownership increases board
independence while Schmidt and Fahlenbrach (2016) find no change in board independence and appointments of
independent directors are met with worse announcement returns when passive institutional ownership increases.
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2. Variable Construction, Data, and Descriptive Statistics
2.1. Construction of institutional investor distraction
We follow Kempf, Manconi, and Spalt (2016) to construct a measure for institutional
investor’s distraction in three steps. For each institutional investor i in a given firm f, we first
identify extreme returns for industry sectors that are unrelated to firm f in investor i’s portfolio.
These unrelated industry shocks are likely to cause investor i to shift his attention away from
firm f. To obtain investor i’s level of distraction away from firm f, we then aggregate these
industry shocks across all the unrelated industry sectors in investor i’s portfolio. Finally, to get
the firm-level distraction measure of firm f, we aggregate the investor-level distraction measure
across all institutional investors of the firm.
Specifically, we define the level of distraction experienced by the institutional investors
of firm f in a given quarter q as:
𝑇𝑜𝑡𝑎𝑙 𝐷𝑖𝑠𝑡𝑟𝑎𝑐𝑡𝑖𝑜𝑛 𝑓,𝑞 = ∑ ∑ 𝑤𝑖,𝑓,𝑞−1×
𝐼𝑁𝐷 ≠𝐼𝑁𝐷𝑓𝑖∈𝑓
𝑤𝑖,𝑞−1𝐼𝑁𝐷
×𝐼𝑆𝑞
𝐼𝑁𝐷
where i denotes firm f’s institutional investor at the end of quarter q-1, IND denotes Fama-
French 12 (FF12) industry sector, and INDf denotes the industry sector in which firm f belongs.
FF12 industry sector represents a broad industry classification. It follows that industry-level
events should generally be unrelated to the fundamentals of individual firms in other FF12
industries.13 𝐼𝑆𝑞𝐼𝑁𝐷 is an indicator variable equals to one if industry IND experiences a shock in
quarter q, and zero otherwise. An industry is deemed to have experienced a shock if the
industry’s return for the quarter is either the highest or lowest across all FF12 industry sectors.
We weight these shocks to capture their economic importance. The variable 𝑤𝑖,𝑞−1𝐼𝑁𝐷 denotes the
weight of industry sector IND in investor i’s portfolio in the prior quarter q-1, which represents
the importance of industry sector IND in institutional investor i’s portfolio.
13 The potential supply-chain links between firms across different Fama-French 12 industries will reduce the
shifts of investor attention to the shocked industries, thus biasing against us finding results.
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The sum of the products of 𝑤𝑖,𝑞−1𝐼𝑁𝐷 and 𝐼𝑆𝑞
𝐼𝑁𝐷 across all industries unrelated to firm f,
capture investor i’s level of distraction away from firm f, when events occur in unrelated
industries of investor i’s portfolio. To aggregate across institutional investors of a firm, we
weight the level of distraction of each investor i in firm f by 𝑤𝑖,𝑓,𝑞−1 which measures the
importance of investor i in firm f in the prior quarter, q-1. Intuitively, investor i have more
weight if 1) firm f has more weight in i’s portfolio and 2) investor i owns a larger fraction of
firm f’s shares. Following Kempf et al. (2016), we compute 𝑤𝑖,𝑓,𝑞−1 as:
𝑤𝑖,𝑓,𝑞−1 = 𝑄𝑃𝐹𝑤𝑒𝑖𝑔ℎ𝑡𝑖,𝑓,𝑞−1 + 𝑄𝑃𝑒𝑟𝑐𝑂𝑤𝑛𝑖,𝑓,𝑞−1
∑ (𝑄𝑃𝐹𝑤𝑒𝑖𝑔ℎ𝑡𝑖,𝑓,𝑞−1 + 𝑄𝑃𝑒𝑟𝑐𝑂𝑤𝑛𝑖,𝑓,𝑞−1)𝑖∈𝐹,𝑞−1
where 𝑃𝐹𝑤𝑒𝑖𝑔ℎ𝑡𝑖,𝑓,𝑞−1 is the weight of the market value of firm f in investor i’s portfolio, and
𝑃𝑒𝑟𝑐𝑂𝑤𝑛𝑖,𝑓,𝑞−1 is investor i’s percentage ownership in firm f. The former measures how much
time the investor is likely to spend in analysing firm f, and the latter measures how much
influence investor i can have in the firm.
We sort all stocks held by investor i into quintiles by 𝑃𝐹𝑤𝑒𝑖𝑔ℎ𝑡𝑖,𝑓,𝑞−1 and all investors
of firm f into quintiles by 𝑃𝑒𝑟𝑐𝑂𝑤𝑛𝑖,𝑓,𝑞−1. 𝑄𝑃𝐹𝑤𝑒𝑖𝑔ℎ𝑡𝑖,𝑓,𝑞−1 and 𝑄𝑃𝑒𝑟𝑐𝑂𝑤𝑛𝑖,𝑓,𝑞−1 takes a
value from 1 to 5 depending on which quintile 𝑃𝐹𝑤𝑒𝑖𝑔ℎ𝑡𝑖,𝑓,𝑞−1 and 𝑃𝑒𝑟𝑐𝑂𝑤𝑛𝑖,𝑓,𝑞−1 ,
respectively, falls in. The weights 𝑤𝑖,𝑓,𝑞−1 sum to 1 for each firm f after scaling by the
denominator. It follows that higher values of Total Distraction indicates that the institutional
shareholders in firm f are more distracted by attention-grabbing returns from unrelated industry
sectors, and therefore their overall monitoring intensity of firm f’s’ board is reduced.
As we have stockholding data and voting data by each individual mutual fund, in
addition to our main firm-level distraction measure, we can also calculate an investor-level
distraction measure for each fund using a similar approach as above so as to examine how fund-
level distractions affect their voting behaviour.
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2.2. Validity of the distraction measure
There are two important advantages of measuring institutional investor distractions in
this way. First, to the extent that the return shocks are in unrelated industries, this measure
captures exogenous variation in institutional shareholder monitoring, since the return shocks
from other FF12 industries are unlikely to be driven by the focal firm’s fundamentals. This
helps to alleviate reverse causality issues and issues relating to omitted variables, which might
affect both institutional investor monitoring levels and firm behaviour. Second, the investor-
level distraction measure differs across the firms held by each investor due to the way it is
constructed. Thus, we are able to compare the within-investor difference in levels of
distractions towards each firm held in the investor’s portfolio, essentially taking into account
the selection issues whereby certain institutions select into firms with specific features due to
their preferences.
We further evaluate whether return shocks in unrelated industries can cause permanent
changes in the focal firm’s board governance and performance. We first check the length of
the extreme industry-level returns, and find that each industry return shock on average only last
for 1.25 quarters and the maximum length of continuous return shocks is only 2 quarters. These
short-lived industry-level return shocks are likely to be random events, and unlikely to cause
institutional investors to significantly rebalance their portfolios. Consistent with our
expectation, Kempf, Manconi, and Spalt (2016) find that the focal firm is unlikely to experience
a large change in its portfolio weight in the institution’s portfolio when the institutional investor
is distracted by events elsewhere. Therefore, unrelated industry shocks are unlikely to drive
changes in the focal firm’s board governance through changes in the stockholdings of the
distracted institutional investor.
Nevertheless, non-shocked industries can continuously experience lowered
institutional investor monitoring intensities for relatively longer periods, as investors
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continuously shift their attention to different shocked industries over time. Suppose a mutual
fund investor has 4 stocks in unrelated industries, for example a bank, a pharmaceutical firm,
a food retailer, and a manufacturing firm. Suppose the pharmaceutical industry experiences a
large return shock in quarter 1, the food retailer experiences a large return shock in quarter 2,
and the manufacturing industry experiences a large return shock in quarter 3. As the mutual
fund manager continuously shifts her attention to different industries other than the financial
services industry, the bank is being “overlooked” during this period. In untablulated analysis,
we find that this distraction period on average lasts for 7 quarters. Thus, looser investor
monitoring due to distractions can lead to significant changes in the focal firm’s board
governance and its long-run operating performance.
2.3. Data and sample formation
Our main sample comes from linking several well-known databases. We start with firm-
years in the RiskMetrics director database, which contains information on board structure and
director characteristics. We obtain information on institutional investor shareholdings from the
Thomson-Reuters Institutional Holdings (13F) database to construct the investor distraction
measure. We then merge the director and institutional holding data with firm accounting and
stock returns data from Compustat and CRSP, respectively. We drop firm-years with missing
information for our distraction measure, board structure, or key financial and stock return
variables. We also exclude the heavily regulated finance and utility industries. Further, we
exclude firms with dual-class share structures and closely-held firms where insiders or directors
as a group hold more than 50% of shares, because institutional shareholders are unlikely to
have much influence on the corporate governance of these firms.14 We focus on independent
14 These exclusions reduce the initial sample size by about 10% and leads to a cleaner sample for the purpose of
our analysis.
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directors in this study because they are the primary board monitors.15 Our final sample consists
of 121,205 independent director-firm-years from 15,575 firm-year observations for the period
1996 to 2013. However, the sample size may vary across tests due to availability of control
variables and dependent variables.
To examine board characteristics and composition, we require CEO-director social ties
information from BoardEx. Although BoardEx has data from 2000, it becomes better populated
only from 2003 and onwards. Therefore, for most of our tests involving board structure, we
start the sample period from 2003 and end in 2013 resulting in 7,663 firm-year observations.
To examine voting outcomes, we also obtain shareholder voting data from ISS Voting
Analytics for the period 2003 to 2012. We merge ISS Voting Analytics with RiskMetrics
director data using company and director names, and further merged this data with CEO-
director social ties information from BoardEx. After requiring non-missing voting data and
social ties data, we end up with 30,310 individual director elections. We call this sample the
director votes sample. In these elections, we observe 21,127 distinct mutual fund-years and
2,081,611 votes.
2.4. Descriptive statistics
Table 1 provides summary statistics for our key variables. Detailed descriptions of all
of the variables can be found in Appendix A. We winsorize all the continuous dependent and
control variables at 1% and 99%. Panel A summarizes the means, medians, 25th and 75th
percentiles, and the standard deviation of the institutional investor distraction measures. For
our fund-level distraction measure, the mean and median mutual fund distraction levels in our
15 We follow the director classification in Riskmetrics. Independent directors are outside directors that have no
family or economic ties to management or the firm they monitor other than that through their directorship.
RiskMetrics primarily relies on the NYSE and Nasdaq listing rules to classify independent directors, and identifies
independent directors based on proxy statements and disclosures of related transactions. Examples of non-
independence using the RiskMetrics definition include but are not limited to: former employees of the firm or
subsidiaries, major shareholders, customers, suppliers, and family members of executives.
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sample are both 0.14, with a standard deviation of 0.06. The mean and median firm-level
distraction measure, Total Distraction, is 0.17 and 0.16 respectively, while the 25th percentile
and 75th percentile values are 0.13 and 0.21, respectively. By construction, Total Distraction
has a minimum value of 0.05. The distribution of our distraction measure across firms is in line
with Kempf, Manconi, and Spalt (2016).
Panel B reports summary statistics for director election outcomes and director
characteristics for our director voting sample with data on voting outcomes and social ties.
Among the 30,310 independent director election votes, on average 5% were “No” votes, i.e.,
defined as “against” or “withheld” votes. Across all director elections, the median director
election sees only 2% of the votes being cast as “No” votes and only 5% cast as negative votes
at the 75th percentile. Therefore, negative votes are rare. At the maximum, 74% of the votes
were negative votes. We also find that only 11% of directors receive a poor voting outcome,
which we define as elections where a director receives more than 10% of “No” votes.
Furthermore, 6% of the ISS director election recommendations are negative. These proposal-
level statistics are similar to those in Cai, Garner, and Walkling (2009).
Almost 25% of the independent directors in the director voting sample are considered
problematic which we define as an independent director who is busy, socially connected to the
CEO, and/or foreign based. A busy director is one who holds 3 or more directorships in total
during the year (Fich and Shivdasani, 2006). Directors who attend the same educational
institutions and/or the same non-business organization as the CEO are deemed to be socially
connected to the CEO.16 A foreign director is one who primarily works for a non-U.S. employer
16 Although BoardEx uses a unique identifier for each of the educational institutions in the database, the same
educational institution may appear under different identifiers (e.g. Harvard University and Harvard Business
School). To remedy this problem, we manually match the names of the educational institutions and create new
identifiers that uniquely identify each educational institution. For shared social ties at non-business organizations,
we include connections at charities, social clubs, and armed forces, and exclude those compulsory professional
and industrial organizations where social interaction is unlikely due to the compulsory nature of membership in
the organizations (e.g. American Bar Association).
15
or last worked for a foreign company if already retired (Masulis, Wang, and Xie, 2012). Among
the problematic directors, 18% are busy directors, 13% are socially dependent directors, and
3% are foreign directors. About 16% of directors leave the board and are not renominated by
the board in the subsequent director elections. We use data from Voting Analytics to determine
whether a particular director is being renominated by the board or not.
In Panel C, we report the director characteristics for our full sample of director-firm-
year observations from 1996 to 2013. We find that only 1% of the independent directors in our
sample have attendance problems defined as missing 25% or more of board meetings.
Independent directors have an average of 1.6 total directorships, while the median number of
directorships is 1. In addition, the average director is 63 years old with board tenure averaging
11 years. Moreover, independent directors generally have weak firm financial incentives with
a director’s mean (median) equity stake in the firm representing only 0.07% (0.02%) of
outstanding shares.
We report board characteristics for the subsample of firm-years with information from
BoardEx. On average 21% of the independent directors on the board are considered
problematic. About 10% of new director appointments and 66% renominations are problematic.
We also look at the distribution of problematic directors on the major committees. On average
about 21% to 22% of the audit, compensation, and nomination committee members are
problematic.
In Panel E, we report descriptive statistics for firm characteristics at the firm-year level.
Boards on average hold 8 meetings per year. The average board has 9 members, out of whom
71% are classified as independent. CEOs own about 2.5% of shares outstanding. Finally, about
60% of the firm-years have a staggered board in our sample.
16
3. Shareholder Distraction and Voting
3.1. Investor-level mutual fund distraction and fund votes
In this section, we examine voting behavior of institutional investors in director
elections as one critical channel of investor monitoring of director quality and performance,
and a disciplinary mechanism for poorly-performing directors. Although the vast majority of
director elections are uncontested and the rejection of a standing director is extremely rare,
Aggarwal, Dahiya, and Prabhala (2015) show poor vote results have disciplinary effects in
themselves. Directors with weak voting support tend to depart from the board and even if they
remain on the board, they get demoted to less important board positions. These poorly-
performing directors also suffer from significant reputational losses in the directorial labor
market in that they gain fewer additional board appointments and lose more of their other board
seats than other independent directors.
We first look at investor-level distraction and their individual voting behavior in Table
2 Panel A. Since 2003, mutual funds are required to publicly disclose their voting behavior
through N-PX filings with the Securities and Exchange Commission (SEC). Therefore, our
analysis of mutual fund voting starts in 2003.17 We focus on actively-managed equity funds as
such funds are most likely to gain from active intervention. We provide more details about the
formation of our voting sample in Appendix B. For each director election proposal, depending
on whether it is under plurality or majority voting, mutual funds can vote “For,” “Against,” or
withhold their vote.18 According to Cai, Garner, and Walkling (2009), shareholders can express
their dissatisfaction by withholding votes, thus “Withhold” is functionally equivalent to
“Against.” Therefore, we classify “Withhold” as well as “Against” votes as “No” or negative
votes. Our dependent variable in Panel A is Oppose Director, which is an indicator variable
17 In the earlier years, Voting Analytics only covers the largest fund families. 18 We include director elections involving plurality voting and majority voting. Under plurality voting,
shareholders can vote “For” or withhold their votes while in majority voting, shareholders can vote “For” or vote
“Against” a director (Ertimur, Ferri, and Oesch, 2015).
17
that equals one if the mutual fund cast a negative vote for a particular director in a given annual
election and is zero otherwise. We find that Oppose Director is equal to one in 6% of cases.
Due to their relative rarity, negative votes by mutual funds should have strong disciplinary
effects on independent directors.
The key independent variable in Table 2 Panel A is Mutual Fund Distraction, which is
the level of distraction experienced by the voting mutual fund in the past four quarters
immediately preceding the voting date. We report linear probability model (LPM) estimates
with two sets of fixed effects and with clustering of standard errors at the fund level. The first
set of fixed effects is interacted fund and year fixed effects, which allows us to compare the
vote outcomes at firms where the voting mutual fund is more distracted against vote outcomes
at firms where the same fund is less distracted during the same year. The second set of fixed
effects are director election proposal fixed effects, which allow us to control for the
characteristics of each election proposal, including time-varying director characteristics and
time-varying firm characteristics including performance. For instance, the ISS
recommendation for the director candidate and shareholder activist events like “just vote no”
campaigns are taken into account using director election proposal fixed effects.
In Model (1) of Panel A, we find that the coefficient on Mutual Fund Distraction is
-0.033 and statistically significant at the 5% level, suggesting that when mutual funds are
distracted, they are less likely to oppose management recommendations in independent director
elections. Economically, a one standard deviation increase (decrease) in institutional investor
distractions reduces the chance that the investor votes against (for) an independent director
candidate in the election by 3.3% (0.033*0.06/6%), adjusted for the unconditional probability
of voting against an election proposal (6%).
We then examine whether problematic directors in particular are less likely to be
disciplined when institutional investors are distracted. We identify three types of independent
18
directors whose monitoring incentives are likely to be compromised. The first type of
problematic director is an independent director who is socially connected to the CEO. Socially
connected directors tend to be friendlier to management and thus, are ineffective monitors
(Hwang and Kim 2009, 2012; Chidambaran, Kedia, and Prabhala, 2011; Fracassi and Tate,
2012; Nguyen, 2012). For example, studies show that CEO-director ties lead to a decline in
CEO turnover-performance sensitivity, and CEOs in such firms also extract more private
benefits, which significantly reduce firm values. The second type of problematic director is an
independent director who is excessively busy due to sitting on multiple boards. Busy directors,
defined as those with 3 or more total directorships during the year, are likely to be
overcommitted and tend to be less effective monitors (Fich and Shivdasani, 2006; Falato,
Kadyrzhanova, and Lel, 2014; Masulis and Mobbs, 2014). The third type of problematic
director is a foreign independent director whose primary employer is a non-US company.
Masulis, Wang and Xie (2012) find that foreign directors are less effective board monitors, and
they tend to miss more board meetings, accept greater earnings management, higher CEO pay,
leading to poor firm performance.
In Models (2) and (3), we split the independent director sample into problematic and
non-problematic candidates. We find that most of the significant effects we found earlier come
from the subsample of problematic director candidates in Model (2), and we observe no
significant effects for non-problematic director candidates in Model (3). Given that most
investors tend to support the director election proposals in general, non-problematic directors
are likely to receive support regardless of whether the investor is distracted. Therefore, we do
not observe a significant impact of mutual fund distraction on voting outcomes for the non-
problematic directors. However, problematic directors often receive less support in general as
vigilant investors vote against these underperforming directors. Yet, when investors are
distracted they tend to ignore the underperformance of these problematic directors and support
19
them in the elections. These findings suggest that directors, especially problematic directors,
are less likely to be disciplined during general elections when mutual fund investors are
distracted.19
Mutual funds within the same fund families may have similar voting patterns. To
account for voting patterns by fund families, we aggregate the mutual fund distraction and
voting behavior at fund family level and report the results in Panel B. The dependent variable
in Panel B is the average of Oppose Director across all funds in the same family, and the key
independent variable is Mean Mutual Fund Distraction, the average distraction of all the funds
in the same family. We use interacted fund family, year fixed effects and election proposal
fixed effects, and standard errors are clustered by fund family. After accounting for the similar
voting patterns within the same mutual fund families, we find similar and consistent evidence
that mutual fund investors are less likely to vote against directors, especially problematic ones,
when they are distracted.
In untabulated tests, we exclude family firms where institutional investors are likely to
have more limited influence and we find that the link between mutual fund distraction and their
voting pattern is stronger. We also use a larger sample where we include both actively-managed
and passively-managed funds. We find that the results are weaker, but remain qualitatively
similar. Additionally, using Bushee’s classification of institution types, we find a stronger
distraction effect for mutual funds that are affiliated to institutions who are more likely to
monitor, such as investment companies, independent investment advisors, and public pension
funds.
19 Another possible measure of ineffective directors is to use ISS recommendations. However, ISS
recommendations have important limitations. For example, ISS have been accused of making “blanket
recommendations” that are uniform recommendations for or against certain types of directors or firm
characteristics. Furthermore, using ISS recommendations to measure ineffective directors would require the
additional assumption that investors are active voters and do not rely on ISS recommendations when they are not
distracted. But this assumption is unlikely to be valid as Iliev and Lowry (2014) find that mutual fund investors
vary greatly on their reliance on ISS recommendations with a substantial portion of funds relying solely on ISS
recommendations.
20
3.2. Firm-level investor distraction and director election results
In Table 3, we examine the impact of distractions by a firm’s institutional investors on
director election outcomes at the firm-level. Our dependent variable is the Fraction of "No"
Votes for a Director and the key independent variable is Total Distraction, defined as the
average distraction of the firm’s institutional investors over the past 4 quarters immediately
before the meeting date. In Models (1) and (2), we examine the impact of investor distraction
on director election outcomes for all independent directors. In Models (3) to (6), we compare
the impact of investor distraction for the election outcomes of problematic versus non-
problematic independent directors. We report LPM estimates and include firm and year fixed
effects in all models as well as director fixed effects in the even-numbered models. We further
control for director and firm characteristics that are likely to affect the director voting results,
and the average fraction of “No” votes for all the independent directors in the firm standing for
election during the year. In all these regressions, we cluster standard errors at the director level.
In Models (1) and (2), we find that the coefficient on Total Distraction is negative and
statistically significant, suggesting that there are fewer “No” votes for director elections when
a firm’s institutional investors are distracted.20 Economically, a one standard deviation increase
in institutional investor distractions increases the negative votes received by a director by 1.7%
to 2.8% (0.014*0.06/5% or 0.023*0.06/5%). For control variables, we find that director
election results are influenced by Average Director “No” Votes, indicating that shareholders’
overall satisfaction with the board members significantly affects individual director election
outcomes. Also, we find that the coefficients on Negative ISS and Poor Meeting Attendance
are positive and significant, which is consistent with the Cai, Garner, and Walking (2009) who
20 Model 2 has fewer observations than Model 1 because directors who only appear once in elections are dropped
in Model 2 with director fixed effects.
21
find that ISS recommendations and director attendance are important determinants of director
voting results.
In Models (3) to (6), we find that the coefficient on investor distraction is statistically
significant for the subsample of problematic independent directors, while it is insignificant for
the subsample of non-problematic directors. The economic magnitude are also much bigger for
the problematic directors. These findings suggest that the effect of investor distraction on
director election outcomes is more pronounced for problematic independent directors, who are
more likely to face negative shareholder assessments.
We then repeat the above analysis using an alternative measure of director disciplinary
vote, Poor Vote Result, as the dependent variable in Panel B. Poor Vote Result is an indicator
variable equals to one if the percent of “No” votes received by a director exceeds 10% of total
votes cast, and zero otherwise.21 We obtain similar results as in Panel A. Economically, a one
standard deviation increase in total distraction leads to a 4.3% or a 4.9% (0.089*0.06/11% or
0.079*0.06/11%) decrease in the likelihood that the independent director receives a poor
election result, after we adjust for the unconditional probability of poor vote result (11%).
Again, the results are concentrated among the sample of problematic directors.
Overall, our findings support the view that directors generally face less pressure to
perform in director elections when institutional investors are distracted, and this effect is more
pronounced for more problematic directors who would have otherwise face more dissent when
investors are more vigilant.
21 The choice of cutoffs is arbitrary. We find similar results using the 30% cutoff as in Aggarwal, Dahiya, and
Prabhala (2015).
22
3.3. Sensitivity of director departures to vote results
Aggarwal, Dahiya, and Prabhala (2015) find that directors are more likely to depart
after they face a more negative shareholder reception in director elections and therefore, annual
elections serve as a potentially important disciplining mechanism for directors. We conjecture
that this disciplinary effect will be weakened when outside institutional investors are distracted.
In Table 4, we examine the impact of shareholder distraction on the sensitivity of director
departures to election results. Our dependent variable is Director Departure, an indicator
variable equals to one if the director is not renominated by the board in the subsequent elections
and zero otherwise.22 We construct this variable by following each director from one election
to the next in Voting Analytics and checking whether the management proposals include
putting up the director for election.23 The focal variables in our analysis are the interaction
terms between Total Distraction and weak vote outcomes, which we measure using Fraction
“No” Votes for a Director and Poor Vote Result Indicator. We only include directors who are
aged 70 and below to exclude departures due to mandatory retirements (Fahlenbrach, Low, and
Stulz, 2016). Since we require vote resultdata for this test, our sample is restricted to directors
who stand up for re-elections at the end of their terms. Thus, our sample is unlikely to include
director departures due to health problems and deaths. We estimate LPMs with either firm and
year fixed effects or director, firm, and year fixed effects. We cluster standard errors at the
director level.
Table 4 Panel A presents the results. Consistent with Aggarwal, Dahiya, and Prabhala
(2015), we find in all models that directors who receive less shareholder support during
elections are less likely to be subsequently renominated. Consistent with our conjecture, we
22 Our results are robust to using a departure indicator using RiskMetrics Director data instead, i.e., we follow
each director from one year to the next in the RiskMetrics Directors database and define a departure as having
occurred if the director is no longer on the board in the subsequent years. 23 We lost some observations because we need to check 2 or 3 subsequent years to see whether the director is
renominated in firms with staggered boards.
23
find that the disciplinary effect of these vote outcomes is attenuated when institutional investors
are distracted. In particular, we find that the coefficients on the interaction terms between Total
Distraction and Fraction of “No” Votes for a Director and Poor Voting Result are negative
and statistically significant in all the columns, suggesting that investor distraction weakens the
sensitivity of director departures to poor election outcomes. In an untabulated analysis, we
interact investor distraction with Poor Meeting Attendance. We find a significant negative
coefficient on the interaction term between Total Distraction and Poor Meeting Attendance,
indicating that directors with poor attendance records are less likely to be replaced when
institutional investors are distracted.
In Panel B of Table 4, we find that the distraction effect on the sensitivity of
independent director departures to weak election outcomes is statistically and economically
stronger in the subsample of problematic directors compared to the non-problematic directors.
This finding is consistent with previous results, which shows that the problematic directors are
less likely to be disciplined when outside investors are distracted.
4. Shareholder Distraction and Board Activities
So far, we have shown that directors are less likely to be disciplined by shareholder
voting when institutional investors are distracted. This should have an impact on their
incentives to diligently monitor management. Therefore, in this section, we examine the impact
of institutional investor distraction on changes in board activities. We measure board activity
by director attendance at board meetings, the frequency of board meetings, composition of
board monitors, and appointments of new problematic directors. Our conjecture is that when
outside institutional investors are distracted and exert less monitoring pressure on the board,
the board reduces their own monitoring efforts by missing more meetings, holding less board
meetings in general, and appointing problematic monitors to the board.
24
4.1. Independent director meeting attendance
We first examine whether institutional investor distraction increases the likelihood of
directors missing board meetings. Attendance records can serve as an important indicator of
the monitoring intensity of outside directors for at least two reasons. First, it is an observable
measure of director performance, which allows us to investigate whether directors behave
differently when one or more major shareholders are distracted. Second, attending board
meetings is a direct way for directors to obtain the information necessary to carry out their
duties and exert influence over firm managers. To the extent that institutional investor
monitoring intensities decline when they shift attention away from the firm, we would expect
to find that directors miss more board meetings.
Table 5 reports results from LPMs where our dependent variable, Poor Meeting
Attendance, is an indicator variable that equals to one if a director has poor board meeting
attendance defined as missing more than 25% of board meetings over the past fiscal year, and
zero otherwise. The key explanatory variable in the regressions is Total Distraction, which
measures the distraction level of the firm’s institutional investors over the past 4 quarters
immediately before the annual meeting date. The control variables used are based on Masulis
and Mobbs (2014). To account for time invariant firm and director characteristics, we include
models with firm fixed effects and models with both director and firm fixed effects. We include
a pre-SOX indicator in place of year fixed effects, to take into account the fact that boards tend
to be more vigilant in the post-SOX era and thus are less likely to miss board meetings. The
pre-SOX indicator is set equal to one for fiscal years 2002 and before, and zero otherwise.
Standard errors are robust and clustered at the director level.24
24 In untabulated test, we include meeting fee and director retainers as additional control variables (the information
on these variables is only available in the period prior to 2006). We also use alternative regression specifications
such as the logit and probit models with industry and year fixed effects. Our results remain unchanged.
25
Our results are reported in Panel A of Table 5. In Models (1) and (2), we find that the
coefficient on Total Distraction is positive and statistically significant, suggesting that
independent directors miss more board meetings when institutional shareholders become
distracted. Economically, a one standard deviation increase in the distraction level leads to a
12% (0.020*0.06/1%) increase in the probability that the director exhibits attendance problems,
after adjusting for the unconditional probability of poor attendance records (1% in our sample).
Among the control variables, the pre-sox indicator is statistically significant at 1% in all
specifications. This result confirms the common belief that the passage of SOX increases
director accountability to shareholders and several studies report that boards tend to be more
vigilant after SOX (e.g., Masulis and Mobbs, 2014). We also find that directors holding a
greater number of directorships tend to miss more board meetings while older directors miss
fewer meetings. This latter result could reflect a selection effect. These findings are in line with
previous studies such as Adams and Ferreira (2009) and Masulis and Mobbs (2014).
To the extent that directors on multiple boards selectively distribute their efforts more
towards larger and more prestigious firms due to reputational concerns (Masulis and Mobbs,
2014), we would expect that directors may not uniformly miss board meetings across all the
boards they sit on when they are not monitored intensively by outside investors. In particular,
we should see a stronger effect of investor distraction on director attendance problems among
smaller firms. In Models (3) and (4), we test this conjecture and include an interaction term
between Total Distraction and firm size. We find that the coefficient on the interaction term is
negative and significant, suggesting that the impact of shareholder distraction on director
frequency of missing meetings is more pronounced in smaller firms.
In Panel B of Table 5, we compare the impact of investor distraction for the attendance
records of problematic versus non-problematic independent directors. For this test, we restrict
the sample period to years 2000 to 2013 when the data on CEO-director social ties is available
26
from BoardEx. The results continue to hold if we start the sample from 2003 when the data is
better populated in BoardEx. The coefficients on total distraction in the subsample of
problematic independent directors are statistically significant in Models (1) and (2), but not
significant in the subsample of non-problematic directors that are reported in Models (3) and
(4). This result indicates that the effect of total distraction is stronger for the subsample of
problematic directors. The poorer attendance performance of problematic directors can be
explained by our findings in Tables 2 to 4 where we find that problematic directors face
significantly weaker disciplinary votes when institutional investors are distracted.25
Overall, we find strong evidence that directors are less attentive when institutional
investors become distracted, particularly in smaller firms where director reputational concerns
are weaker and for problematic directors who face significantly less monitoring when outside
investors are distracted.
4.2. Board meeting frequencies
We next examine how board meeting frequencies are related to institutional shareholder
distractions. Previous studies (Lipton and Lorsch, 1992; Conger et al., 1998; Vafeas 1999)
suggest that board meeting frequency is an important measure of board activity and directors
perform their monitoring duties more diligently if they meet more frequently. As Execucomp
stop reporting board meeting frequency numbers in 2006, we use the MSCI GMI Ratings
database to extend our meeting frequency data for the period from 2007 and onwards. We
perform OLS regressions using the natural logarithm of number of board meetings as the
dependent variable in Models (1) and (2) and include firm and year fixed effects. We also show
25 In an untabulated analysis, we further assess whether poorer attendance by problematic directors is purely driven
by busy directors. We split the busy director sample into busy directors who are also socially connected directors,
and busy, but non-socially connected directors. We find a stronger distraction-poor attendance link among busy
directors that are also socially connected directors. This finding indicates that both busy and social dependent
directors are driving the poorer attendance record of problematic directors.
27
results with industry and year fixed effects using Poisson count models where the dependent
variable is the unlogged number of board meetings. Standard errors are clustered at the firm
level for both types of models.
Our results are reported in Table 6. In Model (1), we find that the coefficient on Total
Distraction is negative and statistically significant, indicating that boards hold fewer meetings
when they are less monitored by outside investors. Vafeas (1999) finds that boards hold more
meetings if the firm is underperforming. Therefore, in Model (2), we examine the sensitivity
of board meeting frequencies to poor firm performance when outside investors are distracted
by including an indicator variable, Poor Tobin’s Q, and its interaction term with Total
Distraction. We find that the coefficient on the interaction term is negative and significant,
indicating that boards are less diligent in trying to improve firm performance when outside
investors are distracted. We find similar results in Models (3) and (4) when we use the Poisson
count model. The number of observations is slightly larger in Models (3) and (4) than in Models
(1) and (2). This is because firms that only appear once in our sample are dropped due to the
firm fixed effects used in Models (1) and (2).
In an untabulated analysis, we use an alternative dependent variable, Fewer Board
Meetings, which is an indicator variable equals to one if the number of board meetings during
the year is less than the number of meetings last year and zero otherwise. We find that investor
distraction significantly increases the likelihood of firms having fewer meetings than before.
4.3. Board composition, new appointments, and renominations of directors
In this subsection, we examine the board composition and appointment of problematic
directors following a change in the level of shareholder attention. Board composition is a key
determinant of board monitoring quality. By appointing effective monitors to the board,
shareholders can be better represented in major corporate decisions, which can ultimately
28
improve firm performance and value. Table 7 reports the regression estimates for the period
2003-2013.26 In Models (1) and (2), we examine the impact of shareholder distraction on board
composition where our dependent variable is Proportion Problematic Directors, which is the
ratio of number of problematic directors to the number of independent directors.
In Model (1), we find that the coefficient on shareholder distraction is positive and
significant, suggesting that firms are more likely to have problematic directors on the board
when the institutional investors are distracted. Given that we control for firm fixed effects, the
coefficients can be interpreted as within-firm changes in board composition. Economically, a
one standard deviation increase in total distraction leads to 1.8% (0.066*0.06/0.21) increase in
the proportion of problematic directors. Previously, we have found that problematic directors
are most likely to benefit from decreased monitoring from distracted institutional investors.
Therefore, in Model (2), we include an interaction term between Total Distraction and the
proportion of problematic independent directors on the nominating committee, Proportion PID
on Nomination Committee. We find that the coefficient on the interaction is positive and
significant, suggesting that the impact of institutional investor distraction on board composition
is more pronounced when there are problematic directors on the nomination committee.
In Models (3) - (6), we further test whether the changes in board composition are driven
by the new appointments or the renominations of problematic directors. The dependent variable
in Models (3) & (4) is New Problematic Director Appointment, an indicator variable equals to
one if the firm has newly appointed at least one problematic independent director during the
year and zero otherwise. The dependent variable in Models (5) & (6) is Renomination of
Problematic Director, an indicator equals to one if the firm has renominated problematic
26 The identification of problematic independent directors requires social ties information from BoardEx that is
available from 2000 and onwards. However, BoardEx significantly increased its coverage in 2003. Furthermore,
the existence of ineffective independent directors on boards and key committees is more relevant after SOX, when
firms are required to have independent boards and 100% independent directors on key committees. Therefore, we
start from Year 2003 for these set of tests.
29
directors and zero otherwise. We estimate LPMs with firm and year fixed effects. The
coefficient on Total Distraction is positive and significant at 5% level in Model (3).
Economically, a one standard deviation increase in total distraction increases the likelihood of
appointing a new problematic director by 13.4% (0.224*0.06/0.10). Furthermore, the impact
of shareholder distraction on appointments of problematic directors is stronger among firms
with more problematic committee members as shown in Model (4). In Models (5) and (6), we
find consistent but weaker evidence for the renomination of problematic directors. Thus the
changes in the board composition is primarily driven by the new appointments of problematic
directors.
In an untabulated analysis, we repeat our analysis in Table 7 and find that distraction
effect is stronger among firms with more CEO power as measured by CEO-chairman duality.
These results are consistent with our conjecture that CEOs and boards take the opportunity
when outside shareholders are distracted to appoint and retain ineffective directors. We also
find that when investors become more distracted, the proportion of problematic directors on
the major monitoring committees (compensation, audit and nomination committees)
significantly increases.
Overall, we find evidence that investor distraction adversely affects board composition,
especially when the nomination committee includes problematic monitors. More specifically,
directors with lower monitoring intensities are more likely to be appointed and renominated to
the board when institutional investors shift their attention away from the firm.
5. Shareholder Distraction and Board Monitoring Effectiveness
So far, we have shown that independent directors, especially problematic directors are
less likely to be disciplined by shareholder votes when institutional investors are distracted.
This leads to boards holding fewer meetings and board members missing more meetings.
30
Boards also appoint and renominate more problematic directors who are less effective
monitors, leading to worse board structures. The decrease in monitoring effectiveness of the
board when shareholders are distracted should manifest itself in the governance outcomes that
fall within the domain of board monitoring activities. In this section, we examine how earnings
management, CEO compensation, and firm valuation are affected by reduced board monitoring
efforts caused by investor distraction. These governance outcomes are often used in the prior
literature to assess board effectiveness.
5.1. Investor distraction and earnings management
We examine the impact of investor distraction on earnings management in Table 8. To
measure earnings management, we follow Dechow, Sloan, and Sweeney (1995) and calculate
a firm’s discretionary accruals.27 We estimate OLS regressions where our dependent variable
is the level of discretionary accruals. We include year fixed effects and firm fixed effects to
control for the time-invariant unobservable firm characteristics that could affect a firm’s
earnings reporting policy. Standard errors are clustered by firm. We find that the coefficient of
Total Distraction is positive and statistically significant, suggesting that firms are able to
pursue more earnings management when institutional investors are distracted.
In Model (2), we interact Total Distraction with the proportion of problematic
independent directors on the audit committee, Proportion PID on Audit Committee, since a
firm’s financial reports are primarily approved by members of this board committee. We find
that the coefficient on the interaction term is positive and significant, suggesting that the impact
of shareholder distraction on earnings management is more pronounced when there are more
27 Using the modified Jones model, discretionary accruals is defined as total accruals minus the predicted value
of total accruals. The predicted value of total accruals is from regressing total accruals on the inverse of total
assets, the difference between change of sales and change of accounts receivable scaled by total assets, and PPE
scaled by total assets. The regression coefficients are estimated cross-sectionally every year for each two-digit
SIC industry.
31
problematic independent directors sitting on the audit committee. In an untabulated test, we
replace the dependent variable with a positive accruals indicator, which equals to one if the
discretionary accruals is positive and zero otherwise. We find similar results.
5.2. Investor distraction and CEO pay
Following Cai, Garner, and Walkling (2009), we define unexplained CEO
compensation as the residual from a regression where the dependent variable is the natural
logarithm of the total CEO compensation and the explanatory variables include log(assets),
ROA, total firm risk, and interacted industry and year fixed effects. The second aspect of CEO
pay we examine is pay-for-performance sensitivity, which is calculated as the CEO's wealth
change from their portfolio of stock and options for a 1% change in firm stock price (Core and
Guay, 2002). In our regressions, we include year fixed effects and firm fixed effects. Standard
errors are clustered by firm.
Table 9 presents the results. In Model (1) where we examine unexplained CEO pay, we
find that the coefficient of institutional investor distraction is positive and statistically
significant at the 1% level, suggesting that CEO pay is higher when a firm’s institutional
shareholders are distracted. Economically, one standard deviation increase in investor
distraction is predicted to increase the likelihood of high excess CEO pay by 4.8%
(0.37*0.06/0.46), after we adjust for the unconditional probability of high CEO pay (46%). We
argue that due to investor distraction, boards have less monitoring incentives and this in turn
leads to lapses in governance. To establish this, we examine whether the impact of investor
distraction on excess pay is stronger when boards monitor less. In Model (2), we interact total
investor distraction with the proportion of problematic independent directors on the
compensation committee since CEO compensation is initially determined by this committee.
We find that the coefficient on this interaction term is positive and significant, indicating that
32
the effect of shareholder distraction on high CEO pay is more pronounced if there are more
problematic independent directors sitting on the compensation committee.
In Model (3) where we examine the CEO pay-for-performance sensitivity, we find that
the coefficient on total investor distraction is negative and significant at the 10% level,
indicating that when investors are distracted, CEOs are less motivated to perform. In Model
(4), we interact Total Distraction with the proportion of problematic directors on the
compensation committee. Although the coefficient on the interaction is in the right direction,
it is insignificant. Kempf, Manconi, and Spalt (2016) find that investor distraction leads to
increases in opportunistically-timed stock options, which have the effect of increasing pay-for-
performance sensitivity instead. Therefore, our weaker results for CEO pay-for-performance
sensitivity can be explained by low CEO pay-for-performance sensitivity and
opportunistically-timed stock options being substitute mechanisms for CEOs to extract private
benefits
In an untabulated test, we also control for the existence of Say-on-Pay proposals. This
information is from Voting Analytics and is available for the period 2003-2012. Our high CEO
pay result remains significant after controlling for Say-on-Pay proposals, but our CEO pay-for-
performance sensitivity results are weaker.
5.3. Investor distraction, reduction in board monitoring efforts and equity evaluation
In Table 10, we use Tobin’s Q as an overall indicator of firm valuation. In Model (1),
we find that the coefficient of Total Distraction is significantly negative, suggesting that firm
equity value is lower when shareholders are distracted. The economic magnitude is also large.
A one standard deviation increase in investor distraction reduces firm value by 6.7%
(2.31*0.06/2.06), relative to the average Tobin’s Q in the sample. This result complements
those of Kempf, Manconi, and Spalt (2016) who find that firms with distracted investors tend
33
to have lower stock return performance. We argue that the underperformance by such firms is
partly caused by reduced board monitoring incentives when investors are distracted.
To identify the exact channel through which shareholder distraction could have an
impact on governance outcomes, we use three proxies to measure board monitoring efforts/
incentives. We have shown that investor distraction on average leads to directors missing more
board meetings therefore, the first measure we use is an indicator variable that equals one if at
least one of the independent directors has a poor meeting attendance record during the fiscal
year, and zero otherwise. Our second variable also measures board monitoring efforts and is
the number of board meetings held during the year. We have also shown that investor
distraction leads to less frequent board meetings, therefore, we want to understand whether the
relation between investor distraction and firm performance is partly caused by boards holding
fewer meetings. Finally, the last variable we use is the proportion of problematic directors on
the board, as we have shown that the problematic independent directors are less likely to face
pressures from outside investors when the investors are distracted.
In Model (2), we find that the negative impact of investor distraction increases when
there is at least one independent director with problematic attendance record. In Model (3), we
do not find that investor distraction decreases firm valuation through a decline in board
meetings. Finally, in Model (4), we look at the proportion of problematic independent directors
on the board. We find that the negative impact of investor distraction on equity valuation is
greater when the board is over-represented by problematic directors who have little incentives
to monitor.
Overall, our findings in Tables 8-10 highlight that board governance is an important
channel through which shareholder distraction can impact governance outcomes and destroy
firm value. When investors are distracted, boards are less pressured to perform, and the boards
34
in turn reduce their monitoring efforts, causing worse governance outcomes and significant
declines in firm value.
6. Robustness Analysis
We conduct multiple robustness checks for our results. In addition to our main
distraction measure, we also calculate several alternative distraction measures. Table 11
summarizes the results. We re-estimate our main results from Tables 3 to 10 and present them
in Panels A to H, respectively. Only the coefficients of the alternative distraction measure are
shown for the sake of brevity. In Column (1), we decompose the firm-level distraction measure
to take into account the type of institutions most likely to monitor managers. The impact of
distraction should be most evident among such monitoring institutions compared to the other
institutional investors who are less likely to perform a monitoring role even in the best of times.
Monitoring Distraction is calculated based on the distraction levels of institutions who are most
likely to monitor such as investment companies, independent investment advisors, and public
pension funds. Our main conclusions continue to hold when we use Monitoring Distraction as
an alternative distraction measure. As an alternative to capturing institutions most likely to
monitor, in untabulated analyses, we also construct distraction metrics based on the firm’s
largest 5, 10, or 20 institutional shareholders to capture only the largest and therefore most
influential shareholders. We find similar results.
In the construction of our main distraction measure, we treat both positive and negative
industry shocks equally. In Columns (2) and (3), we calculate distraction measures
differentiating between positive and negative industry shocks. Distraction (Positive Shocks) is
the distraction level of the institutional investors calculated based only on positive shocks to
other portfolio firms, while Distraction (Negative Shocks) is calculated based only on negative
shocks only. Positive (negative) shocks refer to situations where the industry sector has the
35
highest (lowest) stock returns across all FF12 industry sectors. Overall, we find similar
distraction effects for those two measure. Positive shocks may be equally important as negative
shocks as positive shocks could be linked to major industry restructuring such as mergers and
acquisitions, IPO waves, etc. which require added attention from the institutional investors to
understand the implications of such shocks. Therefore, combining both types of shocks would
be more powerful than separating them.
In Column (4), we employ an alternative distraction measure based on the extreme
trading volume across the FF12 industry sectors. Therefore an industry sector is deemed to
have experienced a shock if the industry has the highest trading volume across all 12 sectors.
We find similar distraction effects for our main results using this measure.
Moreover, we repeat our primary analysis for different subsamples of firms in
untabulated tests. We add back closely-held and dual-class shares firms where institutional
investors have limited influence, and repeat our primary analysis in the full sample of
RiskMetric firms. Consistent with our expectation, the distraction effect is statistically and
economically weaker in this sample since we have included firms with limited institutional
investor power, although Total Distraction remains statistically significant in nearly all of the
cases. We also repeat our primary analysis in a more restrictive sample, by excluding closely-
held, dual-class shares, and family firms. We find statistically and economically stronger
distraction effect in this more restricted sample. However, due to the data availability of family
ownerships, we lose approximately 50% of our sample. Finally, we repeat our main analysis
by adding a control for outside blocks. This variable is from WRDS Blockholder Database and
is only available for the period 1996-2001. Our main results are robust to controlling for outside
blocks.
36
7. Conclusion
We examine whether shareholder distraction weakens board governance. Using
exogenous variations in institutional monitoring intensity caused by time-variation in the level
of attention allocated to stocks in an institutional investor’s portfolio, we find that decreased
institutional monitoring intensity weakens board oversight. In particular, distracted
institutional investors are less likely to use their votes as a disciplining device for ineffective
independent directors. Independent directors on average receive significantly more favorable
votes when outside institutional investors are distracted, and the distraction impact is stronger
for problematic director candidates, who have weaker monitoring qualities. Furthermore,
independent directors, especially problematic directors, are less likely to turnover in response
to poor voting outcomes, implying that the disciplinary effects of voting on independent
directors are weaker in the presence of distracted investors. As a result, board monitoring
intensity declines. Specifically, independent directors miss more meetings and firms with
distracted institutional investors also hold fewer board meetings. Further, firms with distracted
institutional investors allow the appointment of more conflicted or overcommitted independent
directors to the board, and boards become over-represented by problematic directors with less
monitoring effectiveness. Lastly, we find that distracted institutional investors accept greater
earnings management, are more likely to approve high CEO compensation and CEO
compensation structures with less incentive components, and in general are associated with
significantly lower firm valuation. Importantly, the impact of investor distraction on these
governance outcomes are concentrated in those firms with reduction in board monitoring
intensity, suggesting that one of the important channels through which investor distraction
affects firm governance is through their impact on board monitoring efforts.
Overall, we find strong evidence that distracted institutional investors cause poorer
board governance through fewer disciplinary votes in director elections. Boards generally have
37
primary responsibility for monitoring management performance. Our study shows that the
monitor needs to be monitored and that outside shareholder monitoring provides strong
incentives for directors to exert more monitoring efforts and perform their own monitoring
duties effectively.
38
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Table 1: Summary Statistics
The main sample comes from the intersection of RiskMetrics director database, Thomson-Reuters Institutional
Holdings (13F) database, Compustat, and CRSP. We exclude firms with dual-class share structures and closely-
held firms, defined as those where insider ownership is greater than 50% or the total ownership of directors is
greater than 50%. The final sample consists of 121,205 independent director-firm-years and 15,575 firm-year
observations for the period 1996 to 2013. Our sample is further constrained to 30,310 independent director-firm-
years for the period 2003 to 2012 after we require director vote information from Voting Analytics and director
social ties information from BoardEx. Appendix A provides detailed variable descriptions.
Variable N Mean Median 25% 75% STD
Panel A: Distraction Measures
Mutual Fund Distraction 21,127 0.14 0.14 0.1 0.18 0.06
Total Distraction 15,575 0.17 0.16 0.13 0.21 0.06
Panel B: Independent Director Characteristics in the Director Votes Sample (2003-2012)
Fraction "No" Votes for a Director 30,310 0.05 0.02 0 0.05 0.08
Poor Vote Result 30,310 0.11 0 0 0 0.32
Negative ISS 30,310 0.06 0 0 0 0.24
Problematic Director 30,310 0.25 0 0 0 0.41
Director Departure 22,059 0.16 0 0 0 0.36
Panel C: Independent Director Characteristics in the Main Sample (1996-2013)
Poor Meeting Attendance 121,205 0.01 0 0 0 0.12
Number of Directorships 121,205 1.69 1 1 2 1.01
Director Age 121,205 62.61 63 57 68 8
Director Tenure 121,205 11 10 5 15 7.19
Director Own (%) 121,205 0.07 0.02 0 0.08 0.12
Panel D: Board Characteristics (2003-2013)
Proportion Problematic Director 7,663 0.21 0.16 0.00 0.33 0.21
New Problematic Director Appointment 7,663 0.10 0.00 0.00 0.00 0.29
Renomination of Problematic Director 7,663 0.66 1.00 0.00 1.00 0.48
Proportion PID on Compensation Committee 7,663 0.22 0.00 0.00 0.33 0.27
Proportion PID on Audit Committee 7,663 0.21 0.00 0.00 0.33 0.25
Proportion PID on Nomination Committee 7,663 0.22 0.00 0.00 0.33 0.27
Panel E: Board and Firm Characteristics (1996-2013)
Number of Board Meetings 14,027 7.58 7 5 9 3.48
Discretionary Accruals 15,575 0 -0.02 -0.09 0.05 0.41
High CEO Pay 15,575 0.46 0 0 0 0.5
CEO Pay-for-Performance Sensitivity 15,575 36,336 4,261 1,526 12,242 839,879
Tobin’s Q 15,575 2.06 1.61 1.23 2.3 1.53
Board Size 15,575 8.96 9 7 10 2.31
Board Independence 15,575 71.13 75 60 84.62 16.11
CEO Own (%) 15,575 2.46 0.35 0.1 1.39 6.12
Staggered Board 14,113 0.59 1 0 1 0.49
44
Table 2: Mutual Fund Distraction and Fund Votes for Independent Director Election Proposals
This table reports the OLS regression results of fund-level distraction on mutual funds’ votes for independent
director election proposals for the period 2003 to 2012. The sample consists of 2,081,611 fund votes for 30,310
independent director elections in 8,452 shareholder meetings. We include only votes by actively-managed US
domestic equity funds. Appendix B provides details on the sample formation. In Panel A, we show results at
individual fund level. The dependent variable is Oppose Director, which is an indicator variable equals to one if
the mutual fund votes “against” or “withhold” for a particular independent director election proposal, and zero
otherwise. The key independent variable, Mutual Fund Distraction is the fund-level proxy for how much the
mutual fund investor is distracted over the past 4 quarters immediately before the voting date. In Panel B, we
show results aggregated at the fund family level. The dependent variable is the mean of the oppose director
indicator aggregated at fund family level. The independent variable is Mean Mutual Fund Distraction which is
the average fund distraction across all funds in the family. Problematic Directors are independent directors who
hold 3 or more total directorships, are socially-connected to the CEO, and/ or are foreign directors. We use
interacted fund (fund family) and year fixed effects to account for time-varying fund (fund family) characteristics,
and director election proposal fixed effects (equivalent to director-firm-year FE) to account for time-varying
director and firm characteristics. Standard errors are clustered by fund in Panel A and clustered by fund family in
Panel B. ***, **, and * indicates statistical significance of 1%, 5%, and 10% respectively.
Panel A: Mutual Fund Distraction and Individual Fund Votes
All Independent Directors Problematic Directors
Non-problematic
Directors
(1) (2) (3)
Mutual Fund Distraction -0.033** -0.056*** -0.029
(-2.00) (-2.58) (-1.59)
Fund-year FE Y Y Y
Election Proposal FE Y Y Y
Observations 2,081,611 469,888 1,611,723
Adjusted R2 0.353 0.343 0.359
Panel B: Mean Mutual Fund Distraction and Mean Oppose Director Indicator Aggregated at Fund Family Level
All Independent
Directors
Problematic
Directors
Non-problematic
Directors
(1) (2) (3)
Mean Mutual Fund Distraction -0.016 -0.040*** -0.009
(-1.43) (-3.19) (-0.78)
Fund Family-year FE Y Y Y
Election Proposal FE Y Y Y
Observations 967,330 208,828 758,479
Adjusted R2 0.348 0.345 0.352
Table 3: Institutional Investor Distraction and Independent Director Election Outcomes
This table reports OLS regression results for firm-level distraction on independent director election outcomes for
the period 2003 to 2012. The initial sample consists of 30,310 independent director elections in 8,452 shareholder
meetings. The dependent variable in Panel A is Fraction “No” Votes for a Director, which is the number of
“against” and “withhold” votes received by a particular director candidate divided by the sum of “for,” “against,”
and “withhold” votes. The dependent variable in Panel B, Poor Vote Result, is an indicator variable that equals
one if the percent of “against” and “withhold” votes a director candidate receives exceeds 10%, and zero
otherwise. Total Distraction is the average distraction of the firm’s institutional investors over the past 4 quarters
prior to the meeting date. Appendix A provides detailed variable descriptions. Standard errors are clustered by
director. ***, **, and * indicates statistical significance of 1%, 5%, and 10% respectively.
Panel A: Institutional Investor Distraction and Fraction of “No” Votes for a Director
45
All Independent Directors
Problematic Directors
Non-problematic
Directors
(1) (2) (3) (4) (5) (6)
Total Distraction -0.014** -0.023*** -0.044*** -0.061*** -0.005 -0.008
(-2.02) (-2.97) (-2.94) (-3.60) (-0.66) (-0.89)
Negative ISS 0.200*** 0.192*** 0.188*** 0.180*** 0.204*** 0.198***
(76.65) (65.54) (40.76) (34.69) (64.70) (53.61)
Poor Meeting Attendance 0.086*** 0.089*** 0.088*** 0.084*** 0.086*** 0.090***
(12.02) (10.56) (7.12) (6.67) (10.05) (7.71)
Number of Directorships 0.003*** 0.001 0.003*** 0.001 0.002*** 0.000
(8.08) (1.22) (5.88) (0.36) (2.95) (0.32)
Director Tenure 0.002*** 0.001*** 0.002*** 0.001* 0.001*** 0.001
(19.09) (5.30) (10.74) (1.95) (15.86) (1.00)
Director Age 0.000* -0.002 -0.000 -0.003 0.000** -0.001
(1.83) (-1.64) (-0.34) (-1.51) (2.06) (-0.79)
Director Own 0.000 -0.001 -0.000 0.001 0.000 -0.002**
(0.36) (-1.52) (-0.06) (1.52) (0.41) (-2.28)
Average Director "No" Votes 0.050*** 0.051*** 0.052*** 0.052*** 0.049*** 0.050***
(71.56) (65.40) (35.22) (30.57) (61.36) (54.55)
Old Firm -0.000 0.000 -0.005* -0.006** 0.001 0.002
(-0.20) (0.25) (-1.79) (-2.00) (0.63) (1.22)
Ln(Total Assets) -0.005*** -0.003** -0.004 -0.004 -0.005*** -0.004**
(-3.61) (-2.13) (-1.20) (-1.04) (-3.65) (-2.03)
Sales Growth 0.002 -0.001 -0.006 -0.005 0.005 -0.001
(0.61) (-0.28) (-1.03) (-0.78) (1.23) (-0.27)
ROA -0.005 -0.002 0.002 0.002 -0.008* -0.004
(-1.62) (-0.90) (0.64) (0.44) (-1.94) (-1.02)
Institution Own -0.001 -0.002 -0.002 -0.005 0.001 -0.000
(-0.29) (-0.73) (-0.54) (-0.95) (0.47) (-0.07)
Staggered Board -0.002 -0.002 -0.000 -0.001 -0.001 -0.002
(-0.90) (-0.88) (-0.13) (-0.40) (-0.54) (-0.68)
Majority Voting 0.000 0.000 0.002 0.002 -0.001 -0.001
(0.26) (0.41) (1.27) (0.85) (-0.81) (-0.69)
Director FE N Y N Y N Y
Firm FE Y Y Y Y Y Y
Year FE Y Y Y Y Y Y
Observations 30,310 27,479 7,544 6,853 22,556 19,707
Adjusted R2 0.798 0.815 0.803 0.814 0.799 0.812
Panel B: Institutional Investor Distraction and Poor Vote Result
All Independent Directors
Problematic
Directors
Non-problematic
Directors
(1) (2) (3) (4) (5) (6)
Total Distraction -0.089** -0.079* -0.175** -0.237** -0.065 -0.011
(-2.12) (-1.68) (-2.07) (-2.17) (-1.33) (-0.21)
Negative ISS 0.589*** 0.544*** 0.643*** 0.597*** 0.568*** 0.518***
(60.81) (46.85) (40.32) (26.95) (49.55) (36.10)
46
Poor Meeting Attendance 0.223*** 0.243*** 0.191*** 0.227*** 0.232*** 0.249***
(8.91) (8.11) (4.36) (4.15) (7.78) (6.52)
Number of Directorships 0.016*** 0.009* 0.016*** 0.022* 0.009** -0.005
(6.21) (1.66) (4.59) (1.88) (2.53) (-0.58)
Director Tenure 0.005*** 0.004*** 0.006*** 0.003 0.004*** 0.007**
(10.11) (2.94) (7.59) (1.20) (7.49) (2.32)
Director Age 0.000** -0.008 0.000 -0.030** 0.001** -0.011
(2.06) (-0.87) (1.05) (-2.12) (2.19) (-0.65)
Director Own 0.001 -0.001 -0.002 0.001 0.002** -0.002
(1.04) (-0.54) (-0.63) (0.43) (2.33) (-0.70)
Average Director "No" Votes 0.206*** 0.212*** 0.208*** 0.213*** 0.205*** 0.211***
(50.59) (44.80) (27.13) (19.96) (44.04) (37.91)
Old Firm -0.020** -0.021** -0.025 -0.042* -0.018* -0.016
(-2.38) (-2.28) (-1.62) (-1.96) (-1.89) (-1.42)
Ln(Total Assets) -0.017** -0.013 -0.014 -0.010 -0.017* -0.014
(-1.98) (-1.27) (-0.81) (-0.41) (-1.72) (-1.23)
Sales Growth -0.009 -0.012 0.005 -0.024 -0.005 -0.008
(-0.49) (-0.56) (0.15) (-0.55) (-0.25) (-0.33)
ROA -0.027 -0.020 -0.010 0.042 -0.056** -0.059**
(-1.44) (-0.89) (-0.80) (1.30) (-2.34) (-2.08)
Institution Own 0.016 0.009 0.049*** 0.035 0.012 0.009
(1.31) (0.69) (3.16) (0.87) (0.83) (0.54)
Staggered Board -0.012 -0.013 -0.012 -0.010 -0.010 -0.022
(-0.99) (-0.97) (-0.68) (-0.37) (-0.76) (-1.35)
Majority Voting 0.023*** 0.024*** 0.036*** 0.024* 0.021*** 0.023***
(4.15) (3.95) (3.55) (1.92) (3.13) (3.09)
Director FE N Y N Y N Y
Firm FE Y Y Y Y Y Y
Year FE Y Y Y Y Y Y
Observations 30,310 27,479 7,544 6,853 22,556 19,707
Adjusted R2 0.544 0.559 0.555 0.560 0.545 0.548
47
Table 4: Investor Distraction and the Sensitivity of Independent Director Departure to Weak
Election Outcomes
This table reports OLS regression results of the effect of institutional investor distraction on the sensitivity of
independent director departure to director election votes for the period 2003 to 2012. We only include independent
directors who are aged below 70 in this analysis, to ensure their departures are not due to mandatory retirement.
The dependent variable in Panels A and B is Director Departure, an indicator variable that equals to one if the
independent director is not renominated by the board in the subsequent elections and zero otherwise. Total
Distraction is the average distraction of the firm’s institutional investors over the past 4 quarters immediately
before the annual shareholder meeting date. Fraction of "No" Votes for a Director, is the number of “against” and
“withhold” votes received by a particular director candidates divided by the sum of “for,” “against,” and “withhold”
votes. Poor Vote Result is an indicator variable that equals to one if the percent of “against” and “withhold” votes
received by a director candidate is more than 10%, and zero otherwise. Appendix A provides detailed variable
descriptions. Standard errors are clustered by director. ***, **, and * indicates statistical significance of 1%, 5%,
and 10% respectively.
48
Panel A: Investor Distraction and the Sensitivity of Departure to Weak Election Outcomes
(1) (2) (3) (4)
Total Distraction: a 0.114 0.094 0.046 0.055
(1.31) (1.12) (0.67) (0.84)
Fraction “No” Votes for a Director: b 0.032*** 0.026***
(3.73) (2.95)
a * b -0.140*** -0.106**
(-2.83) (-2.18)
Poor Vote Result: c 0.055*** 0.056***
(3.11) (3.04)
a * c -0.320*** -0.301***
(-3.13) (-2.96)
Number of Directorships 0.006** 0.017** 0.006** 0.017**
(2.08) (2.53) (2.22) (2.55)
Major Committee -0.029*** 0.020 -0.028*** 0.021
(-2.90) (1.58) (-2.80) (1.60)
Director Own 0.046* -0.064 0.048* -0.066
(1.85) (-1.18) (1.91) (-1.22)
Director Age -0.034 -1.581*** -0.034 -1.595***
(-1.62) (-2.59) (-1.59) (-2.61)
Director Tenure 0.049*** 0.087*** 0.050*** 0.087***
(10.17) (5.78) (10.55) (5.77)
Institution Own 0.025 0.009 0.024 0.008
(1.26) (0.50) (1.20) (0.43)
Old Firm -0.017 -0.005 -0.017 -0.005
(-1.15) (-0.29) (-1.16) (-0.30)
Ln(Total Assets) 0.047*** 0.007 0.047*** 0.007
(4.61) (0.56) (4.59) (0.56)
Sales Growth -0.104*** -0.053** -0.102*** -0.051*
(-4.07) (-2.00) (-3.98) (-1.94)
ROA 0.014 0.023 0.013 0.023
(0.54) (0.86) (0.50) (0.85)
Tobin's Q 0.015*** 0.009** 0.015*** 0.009**
(4.09) (2.39) (4.06) (2.38)
Firm Risk 0.033*** 0.030*** 0.033*** 0.029***
(7.29) (6.29) (7.26) (6.26)
Board Size 0.019*** 0.002 0.019*** 0.002
(7.24) (0.77) (7.27) (0.78)
Board Independence 0.000 -0.000 0.000 -0.000
(1.03) (-0.36) (0.97) (-0.39)
Majority Voting -0.031*** -0.023** -0.032*** -0.024**
(-3.46) (-2.33) (-3.58) (-2.43)
Director FE N Y N Y
Firm FE Y Y Y Y
Year FE Y Y Y Y
Observations 22,059 19,789 22,059 19,789
Adjusted R2 0.358 0.334 0.358 0.334
49
Panel B: Investor Distraction and the Sensitivity of Departure to Weak Election Outcomes: Problematic vs. Non-
problematic Directors
Problematic directors Non-problematic directors
(1) (2) (3) (4)
Total Distraction: a 0.350** 0.198 0.028 0.003
(1.98) (1.13) (0.28) (0.03)
Fraction “No” Votes for a Director: b 0.029* 0.017 0.025*** 0.020**
(1.76) (0.96) (2.66) (2.03)
a * b -0.186** -0.126 -0.091 -0.063
(-1.96) (-1.33) (-1.62) (-1.13)
Other Controls in Panel A Y Y Y Y
Director FE N Y N Y
Firm FE Y Y Y Y
Year FE Y Y Y Y
Observations 5,776 4,941 16,283 14,848
Adjusted R2 0.324 0.333 0.357 0.304
50
Table 5: Institutional Investor Distraction and Independent Directors’ Meeting Attendance
This table reports results of institutional investor distraction on individual independent director’s attendance at
board meetings from OLS regressions for 1996-2013. The dependent variable is Poor Meeting Attendance, an
indicator variable that equals to one if an independent director attended fewer than 75% of a firm’s board meetings
during the past fiscal year, and zero otherwise. Total Distraction is the average distraction of the firm’s
institutional investors over the past 4 quarters immediately before the annual meeting date. Panel A reports results
using the full sample. Panel B examines subsamples of problematic directors and non-problematic directors. The
sample period in Panel B is 2000-2013, because CEO-director social ties information from BoardEx that is used
to construct the problematic director variable is only available set for this period. Appendix A provides detailed
variable descriptions. Standard errors are clustered by director. ***, **, and * indicates statistical significance of
1%, 5%, and 10% respectively.
Panel A: Institutional Investor Distraction and Poor Director Meeting Attendance
(1) (2) (3) (4)
Total Distraction: a 0.020*** 0.020** 0.203** 0.230***
(2.68) (2.52) (2.47) (2.78)
Ln(Total Assets): b -0.005*** -0.003* -0.004*** -0.001
(-3.95) (-1.78) (-2.94) (-0.79)
a * b -0.008** -0.009**
(-2.28) (-2.57)
Pre-SOX 0.011*** 0.006*** 0.011*** 0.006***
(9.14) (3.98) (9.22) (4.03)
Number of Directorships 0.002*** 0.002** 0.002*** 0.002**
(3.47) (2.48) (3.50) (2.49)
Director Own 0.000 -0.001** 0.000 -0.001**
(0.17) (-2.01) (0.28) (-2.02)
Director Age -0.021*** -0.063*** -0.021*** -0.065***
(-4.89) (-3.34) (-4.93) (-3.46)
Director Tenure -0.001 0.003* -0.001 0.003*
(-0.68) (1.85) (-0.66) (1.95)
Board Size 0.002*** 0.001*** 0.002*** 0.001***
(4.95) (3.84) (5.08) (3.94)
Old Firm 0.000 0.004 0.000 0.004
(0.15) (1.41) (0.12) (1.37)
Sales Growth 0.002 -0.003 0.001 -0.003
(0.41) (-0.68) (0.35) (-0.71)
ROA -0.005* -0.005 -0.005 -0.005
(-1.65) (-1.53) (-1.49) (-1.53)
Institution Own -0.009*** -0.005** -0.008*** -0.005**
(-3.51) (-2.04) (-3.34) (-2.03)
Tobin's Q 0.001 0.001* 0.000 0.001*
(1.21) (1.71) (0.89) (1.72)
Director FE N Y N Y
Firm FE Y Y Y Y
Year FE N N N N
Observations 121,205 117,592 121,205 117,592
Adjusted R2 0.035 0.129 0.030 0.130
51
Panel B: Institutional Investor Distraction and the Poor Meeting Attendance of Problematic vs Non-Problematic
Directors
Problematic Directors Non-problematic Directors
(1) (2) (3) (4)
Total Distraction 0.027* 0.032* 0.012 0.011
(1.67) (1.95) (1.39) (1.05)
Other Controls in Panel A Y Y Y Y
Director FE N Y N Y
Firm FE Y Y Y Y
Year FE N N N N
Observations 24,596 23,958 65,349 62,878
Adjusted R2 0.036 0.146 0.027 0.113
52
Table 6: Investor Distraction and Board Meeting Frequencies
This table reports results of institutional investor distraction on firm-level board meeting frequencies from OLS
regressions (Models (1) and (2)) and Poisson regressions (Models (3) and (4)). The sample covers firms in the
RiskMetrics universe for the period 1996-2013, where the information on board meeting frequencies is from
ExecuComp for 1996-2006 and MSCI GMI Ratings for 2007-2013. The dependent variable in all models is
Number of Board Meetings, which is the number of board meetings over the current fiscal year, and we take the
natural logarithm of this number in Models (1) and (2). Poor Tobin's Q is an indicator variable equals to one if
the firm’s Tobin’s Q is below the bottom quartile of all firms during that year and zero otherwise. Total Distraction
is the average distraction of the firm’s institutional investors over the prior fiscal year. Standard errors are clustered
by firm. Appendix A provides detailed variable descriptions. ***, **, and * indicates statistical significance of
1%, 5%, and 10% respectively.
OLS Poisson
(1) (2) (3) (4)
Total Distraction: a -0.209* -0.195** -0.295** -0.309**
(-1.73) (-2.26) (-2.14) (-2.21)
Poor Tobin's Q: b 0.054*** 0.082***
(2.88) (3.17)
a * b -0.176* -0.248*
(-1.70) (-1.79)
Acquisition Dummy 0.027*** 0.029*** 0.036*** 0.040***
(4.56) (5.16) (5.08) (5.58)
Board Size -0.001 -0.002 -0.047* -0.051*
(-0.47) (-0.95) (-1.75) (-1.94)
Board Independence 0.001** 0.001*** 0.002*** 0.002***
(1.98) (2.73) (4.50) (4.35)
Staggered Board 0.020 0.019 0.001 -0.000
(1.00) (1.44) (0.08) (-0.02)
Old Firm 0.010 0.011 -0.007 -0.008
(0.77) (1.22) (-0.61) (-0.67)
Ln(Total Assets) 0.027** 0.031*** 0.036*** 0.036***
(2.43) (4.78) (6.94) (7.03)
Sales Growth -0.095*** -0.093*** -0.132*** -0.119***
(-3.43) (-4.28) (-4.10) (-3.67)
ROA -0.076** -0.072*** -0.124*** -0.109***
(-1.99) (-3.51) (-2.96) (-2.59)
Institution Own -0.012 -0.007 -0.011 -0.017
(-0.39) (-0.32) (-0.58) (-0.91)
Industry FE N N Y Y
Firm FE Y Y N N
Year FE Y Y Y Y
Observations 13,859 13,859 13,972 13,972
Adjusted R2 0.108 0.111 NA NA
53
Table 7: Investor Distraction, Board Composition, and Appointments or Renominations of
Directors
This table reports results of institutional investor distraction on board composition and independent director
appointments for the period 2003 to 2013. The dependent variable in Models (1) and (2) is Proportion Problematic
Directors, which is the proportion of problematic directors among the independent directors on the board.
Problematic Directors are independent directors who hold 3 or more total directorships, are socially-connected to
the CEO, and/ or are foreign directors. The dependent variable in Models (3) and (4) of Panel A is New
Problematic Director Appointment, an indicator variable equals to one if the firm has newly appointed at least
one problematic independent director, and zero otherwise. The dependent variable in Models (5) and (6) is
Renomination of Problematic Director, an indicator variable that equals to one if the firm has renominated
problematic directors during the year and zero otherwise. Proportion PID on Nomination Committee is calculated
as the proportion of problematic directors among the independent directors on the nomination committees. Total
Distraction is the firm-level proxy for how much institutional investors are distracted over the past 4 quarters
immediately before the annual meeting date. Appendix A provides detailed variable descriptions. Standard errors
are clustered by firm. ***, **, and * indicates statistical significance of 1%, 5%, and 10% respectively.
Dependent variable=
Proportion Problematic
Directors New Problematic
Director Appointment Renomination of
Problematic Director
(1) (2) (3) (4) (5) (6)
Total Distraction: a 0.066* -0.021 0.224** -0.034 0.269* 0.196
(1.71) (-0.55) (2.08) (-0.31) (1.69) (1.06)
Proportion PID on
Nomination
Committee: b
0.231*** 0.164*** 0.104*** -0.093 0.227*** 0.171**
(17.54) (5.89) (4.21) (-1.46) (6.16) (2.16)
a * b 0.388*** 1.154*** 0.330
(2.75) (3.26) (0.81)
Staggered Board 0.014 0.012 0.032 0.028 0.021 0.020
(1.03) (0.92) (1.33) (1.16) (0.48) (0.45)
Board Independence 0.009 0.009 -0.037 -0.040 0.065 0.064
(0.72) (0.66) (-1.00) (-1.07) (1.42) (1.40)
Board Size -0.000 -0.000 -0.033*** -0.033*** 0.006 0.006
(-0.04) (-0.04) (-7.22) (-7.20) (1.01) (1.01)
Old Firm -0.007 -0.007 0.005 0.004 -0.079** -0.080**
(-0.72) (-0.77) (0.27) (0.20) (-2.17) (-2.17)
Ln(Total Assets) 0.019*** 0.019*** 0.060*** 0.060*** 0.074*** 0.074***
(2.73) (2.73) (4.39) (4.40) (2.88) (2.88)
Sales Growth 0.023 0.023 0.053 0.052 -0.061 -0.061
(1.63) (1.61) (1.22) (1.21) (-0.89) (-0.89)
ROA -0.044*** -0.043** -0.052 -0.050 -0.005 -0.005
(-2.58) (-2.56) (-1.20) (-1.18) (-0.07) (-0.07)
Institution Own 0.020** 0.020** -0.010 -0.010 -0.042 -0.041
(1.98) (2.00) (-0.39) (-0.38) (-0.99) (-0.99)
Firm FE Y Y Y Y Y Y
Year FE Y Y Y Y Y Y
Observations 7,663 7,663 7,663 7,663 7,663 7,663
Adjusted R2 0.770 0.770 0.080 0.082 0.311 0.311
54
Table 8: Institutional Investor Distraction and Earnings Management
This table reports the OLS regression results of institutional investor distraction on firm’s earnings management
the period 1996 to 2013. The dependent variable in Model (1) is Discretionary Accruals, where discretionary
accruals are calculated using the modified Jones model as in Dechow, Sloan, and Sweeney (1995). Proportion
PID on Audit Committee is calculated as the proportion of problematic directors among the independent directors
on the audit committee, which is available only for the period 2003-2013 due to BoardEx data availability. Total
Distraction is the firm-level proxy for how much institutional investors are distracted over the prior fiscal year.
Appendix A provides detailed variable descriptions. Standard errors are clustered by firm in all regressions. ***,
**, and * indicates statistical significance of 1%, 5%, and 10% respectively.
(1) (2)
Total Distraction: a 0.274*** -0.103
(3.54) (-0.87)
Proportion PID on Audit Committee: b -0.122**
(-2.14)
a * b 0.688**
(2.04)
CEO Own 0.004 0.012
(0.51) (0.91)
Old Firm -0.006 -0.018
(-0.37) (-0.40)
Ln(Total Assets) -0.019*** -0.053***
(-2.63) (-3.37)
Sales Growth 0.069*** 0.091**
(3.18) (2.29)
ROA 0.053** 0.028
(2.12) (0.57)
Tangibility 0.031 0.008
(0.90) (0.14)
Leverage -0.011 -0.023
(-0.61) (-0.74)
Tobin’s Q -0.002 -0.011*
(-0.81) (-1.91)
Board Independence 0.002 0.027
(0.18) (1.04)
Board Size -0.004 0.017
(-0.21) (0.45)
Institutional Own 0.017*** 0.008
(3.80) (1.23)
Firm FE Y Y
Year FE Y Y
Observations 15,575 7,663
Adjusted R2 0.054 0.053
55
Table 9: Institutional Investor Distraction and CEO Pay
This table reports the OLS regression results of how institutional investor distraction affects board monitoring
effectiveness and firm performance through lower director monitoring effects. The dependent variable in Models
(1) and (2) is High CEO Pay, an indicator variable equals one if the abnormal CEO compensation during the year
is greater than the median abnormal pay in the sample, and zero otherwise. Abnormal CEO compensation is the
residual from an OLS regression where the dependent variable is the natural logarithm of the total CEO
compensation and the independent variables include log(assets), ROA, total firm risk, and interacted industry-
year dummies. The dependent variable in Models (3) and (4) is the natural logarithm of one plus CEO pay-for-
performance sensitivity, where the pay-for-performance sensitivity is the CEO's wealth change from stock and
option holdings for a 1% increase in company stock. Total Distraction is the firm-level measure for how much
institutional investors are distracted over the prior fiscal year. Proportion PID on Compensation Committee is the
proportion of problematic independent directors on the compensation committee. Appendix A provides detailed
variable descriptions. Standard errors are clustered by firm in all regressions. ***, **, and * indicates statistical
significance of 1%, 5%, and 10% respectively.
High CEO Pay
Ln(1+CEO Pay-for-
Performance
Sensitivity)
(1) (2) (3) (4)
Total Distraction: a 0.371*** 0.248 -1.015* 0.091
(2.92) (1.21) (-1.82) (0.10)
Proportion PID on Compensation Committee: b -0.104 0.322
(-1.10) (0.92)
a * b 0.871* -1.361
(1.79) (-0.75)
CEO Own -0.011 -0.011 0.359*** 0.305***
(-0.96) (-0.73) (7.50) (4.70)
Old Firm -0.040* -0.043 -0.241** -0.217*
(-1.67) (-1.33) (-2.45) (-1.75)
Ln(Total Assets) -0.006 -0.002 0.677*** 0.811***
(-0.41) (-0.07) (12.91) (9.59)
Sales Growth 0.092** 0.184*** 0.319* -0.204
(2.22) (2.71) (1.95) (-0.78)
ROA 0.270*** 0.355*** 0.719*** 0.909**
(4.27) (3.40) (3.72) (2.33)
Tangibility -0.101* -0.162* 0.311 0.190
(-1.93) (-1.80) (1.53) (0.62)
Leverage -0.050* -0.157*** -0.291** -0.539***
(-1.67) (-3.06) (-2.17) (-3.69)
Tobin’s Q 0.040*** 0.051*** 0.341*** 0.477***
(7.94) (5.03) (14.02) (9.93)
Board Independence 0.057*** 0.098** -0.161** 0.008
(2.62) (2.32) (-1.97) (0.06)
Board Size -0.037 -0.090* -0.077 0.106
(-1.00) (-1.74) (-0.58) (0.51)
Institution Own 0.008 0.000 0.149 0.051
(0.91) (0.02) (1.63) (1.18)
Firm FE Y Y Y Y
Year FE Y Y Y Y
Observations 15,575 7,663 15,575 7,663
Adjusted R2 0.353 0.336 0.306 0.347
56
Table 10: Institutional Investor Distraction and Equity Valuation This table reports the OLS regression results of how institutional investor distraction affects board monitoring
effectiveness and firm performance through lower director monitoring effects. The dependent variable in all
columns is Tobin’s Q, which is the market value of a firm’s total assets divided by the book value of total assets.
Total Distraction is the firm-level measure for how much institutional investors are distracted over the prior fiscal
year. ID with Poor Meeting Attendance is an indicator variable equals to one if at least one independent director
attended fewer than 75% of board meetings during the year, and 0 otherwise. Number of Board Meetings is the
number of board meetings over the current fiscal year. Proportion Problematic Director is the proportion of
problematic directors among the firm’s independent directors. Appendix A provides detailed variable descriptions.
Standard errors are clustered by firm in all regressions. ***, **, and * indicates statistical significance of 1%, 5%,
and 10% respectively.
(1) (2) (3) (4)
Total Distraction: a -2.310*** -2.023*** -3.846** -0.079
(-5.05) (-4.53) (-2.51) (-0.28)
ID with Poor Meeting Attendance: b 0.090
(0.91)
a * b -0.896*
(-1.80)
Number of Board Meetings: c -0.283**
(-2.02)
a * c 0.768
(1.10)
Proportion Problematic Director: d 0.532**
(2.39)
a * d -3.036***
(-2.80)
CEO Own 0.062** 0.061** 0.049* 0.008
(2.18) (2.16) (1.69) (0.30)
Old Firm 0.002 0.003 -0.002 -0.007
(0.03) (0.05) (-0.03) (-0.13)
Ln(Total Assets) -0.587*** -0.587*** -0.579*** -0.480***
(-9.21) (-9.26) (-8.78) (-9.35)
Sales Growth 1.274*** 1.270*** 1.304*** 0.422***
(6.00) (5.99) (6.19) (2.58)
ROA 1.902*** 1.896*** 1.777*** 2.604***
(3.86) (3.86) (3.69) (4.83)
Institution Own 0.042* 0.043** 0.040* 0.001
(1.96) (2.06) (1.79) (0.08)
Tangibility -0.037 -0.041 -0.026 -0.397**
(-0.22) (-0.25) (-0.16) (-2.43)
Leverage -0.495*** -0.493*** -0.470*** -0.399***
(-4.36) (-4.34) (-4.06) (-4.10)
Board Independence 0.010 0.007 0.010 0.075
(0.17) (0.12) (0.17) (1.31)
Board Size -0.349*** -0.339*** -0.364*** -0.214**
(-3.74) (-3.65) (-3.81) (-2.48)
Firm FE Y Y Y Y
Year FE Y Y Y Y
Observations 15,575 15,575 14,027 7,663
Adjusted R2 0.622 0.622 0.629 0.761
57
Table 11: Robustness Checks Using Alternative Investor Distraction Measures This table reports our main results using alternative institutional investor distraction measures as a robustness
check. Monitoring Distraction is calculated based on the distraction levels of institutions who are most likely to
monitor such as investment companies, independent investment advisors, and public pension funds. Distraction
(Positive Shocks) and Distraction (Negative Shocks) are firm-level distraction measures that are calculated based
on positive industry-level return shocks and negative industry-level return shocks, respectively. Volume-based
Distraction is a distraction measure calculated based on extreme trading volume across the FF12 industry sectors
instead of return shocks. All regressions include the control variables that are used in the respective tables
previously. Panels A and B also include director, firm, and year fixed effects. Panel C include director and firm
fixed effects. Panels D to H include firm and year fixed effects. Appendix A provides detailed variable
descriptions. Standard errors are clustered by firm in all regressions. ***, **, and * indicates statistical
significance of 1%, 5%, and 10% respectively.
Alternative Distraction Variable =
Monitoring
Distraction
(1)
Distraction
(Positive
Shocks)
(2)
Distraction
(Negative Shocks)
(3)
Volume-based
Distraction
(4)
Panel A: Dep Var = Fraction "No" Votes for a Director
Alternative Distraction Variable -0.024*** -0.024*** -0.027*** -0.023**
(-3.16) (-2.75) (-2.91) (-2.43)
Panel B: Dep Var = Non-Renomination Indicator
Fraction "No" Votes for a Director: a 0.027*** 0.029*** 0.017* 0.040***
(2.98) (3.52) (1.75) (4.15)
Alternative Distraction Variable: b 0.211** 0.301*** 0.040 -0.145
(2.43) (3.11) (0.36) (-1.29)
a * b -0.133*** -0.178*** -0.080 -0.230***
(-2.70) (-3.36) (-1.24) (-3.89)
Panel C: Dep Var = Poor Director Attendance Indicator
Alternative Distraction Variable 0.020** 0.022** 0.024** 0.039***
(2.60) (2.52) (2.33) (3.79)
Panel D: Dep Var = Ln(Number of Board Meetings)
Alternative Distraction Variable -0.226* -0.224* -0.273* -0.262
(-1.92) (-1.75) (-1.72) (-1.60)
Panel E: Dep Var = Proportion Problematic Directors
Alternative Distraction Variable 0.127* 0.156* 0.170* 0.228*
(1.70) (1.73) (1.85) (1.95)
Panel F: Dep Var = Discretionary Accruals
Alternative Distraction Variable 0.300*** 0.478*** 0.052 0.508***
(3.86) (5.08) (0.61) (4.68)
Panel G: Dep Var = High CEO Pay
Alternative Distraction Variable 0.373*** 0.396*** 0.458*** 0.421**
(2.98) (2.95) (2.75) (2.24)
Panel H: Dep Var = Tobin's Q
Alternative Distraction Variable -2.299*** -2.766*** -2.372*** -3.514***
(-4.99) (-5.22) (-4.64) (-5.26)
Appendix A: Variable Definitions
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Variable Definition
Panel A: Distraction Measures
Mutual Fund Distraction Fund-level proxy for how much the mutual fund is distracted over the
4 quarters immediately before the voting date. It is the weighted average
return shocks across Fama-French 12 industries, unrelated to the focal
firm, held by the mutual fund. The weights are based on the investor’s
portfolio weights in the shocked industries.
Total Distraction Firm-level proxy for how much institutional investors are distracted
over the past 4 quarters immediately before the annual meeting
date/fiscal year end. It is the weighted average distraction of
institutional investors in the firm. We calculate the investor-level
distraction measure as the weighted average return shocks across
industries, unrelated to the focal firm, held by the investor. The return
shocks are weighted by the investor’s portfolio weights in the shocked
industries.
Panel B: Director Characteristics
Director Age Director's age.
Director Departure An indicator variable that equals to one if the independent director is
not renominated by the board in the subsequent elections and zero
otherwise.
Director Own Director's percentage ownership in the firm obtained from RiskMetrics
Director database.
Director Tenure Number of years the director has been on the board.
Fraction "No" Votes for a Director The number of “against” and “withhold” votes received by a particular
director candidate divided by the sum of “for,” “against,” and
“withhold” votes. This variable is at the firm-director-election date
level.
Major Committee Indicator variable equals one if the director is a member of the
nominating, audit, compensation, or corporate governance committee.
Negative ISS Indicator variable equals to one if the ISS recommendation for the
director candidate is either “against” or “withhold,” and zero otherwise.
Number of Directorships Number of directorships held by the director within the RiskMetrics
universe during the year, including the focal firm.
Oppose Director Indicator variable equals one if the mutual fund votes “against” or
“withhold” for a particular director candidate, and zero otherwise. This
variable is at the fund-firm-director-election date level.
Poor Meeting Attendance Indicator variable equals one if the director attended less than 75% of
the board meetings during the year, and zero otherwise.
Poor Vote Result Indicator variable equals one if the percent of “against” and “withhold”
votes is more than 10% of total votes cast, and zero otherwise.
Problematic Director Indicator variable equals to one if the independent director holds 3 or
more directorships during the year, if the director shares a social tie with
the current CEO, or if the independent director is a foreign director, and
zero otherwise. A social tie exists if the CEO and director attend a
common educational institution or are members of the same non-
business organization. A foreign director is one whose primary
employer is a non-U.S. entity.
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Panel C: Firm Characteristics
Acquisition Dummy Indicator variable equals one if the firm has announced an acquisition
during the fiscal year.
Average Director "No" Votes The mean fraction of “against” and “withhold” votes received by all the
independent directors in the firm in a particular year. This variable is at
the firm-election date level.
Board Size Number of directors on the board.
Board Independence Percentage of board members who are independent directors using the
RiskMetrics classification.
CEO-Chairman Duality Indicator variable equals one if the CEO is also the chairman of the
firm's board, and zero otherwise.
CEO Own CEO’s percentage ownership in the firm.
CEO pay-for-performance
sensitivity
CEO's dollar wealth change from stock and option holdings for a 1%
increase in company stock price plus one (Core and Guay, 2002). In
thousands of dollars.
Discretionary Accruals A proxy for earnings management calculated using the modified Jones
model as in Dechow, Sloan, and Sweeney (1995).
Firm Risk The natural logarithm of the variance of daily returns over firm fiscal
year.
High CEO Pay An indicator variable equals one if the abnormal CEO compensation is
greater than the median abnormal pay in the sample, and zero
otherwise. Abnormal CEO compensation is the residual from an OLS
regression where the dependent variable is the natural logarithm of the
total CEO compensation and the control variables include log(assets),
ROA, total firm risk, and industry-year dummies.
ID with Poor Meeting Attendance An indicator variable equals to one if at least one independent director
attended fewer than 75% of board meetings during the year, and 0
otherwise.
Institution Own Total percentage ownership from all institutional investors.
Leverage (Total current debt + long term debt)/ beginning-year total assets.
Majority Voting An indicator variable equals to one if the firm requires the director to
receive more than 50% “Yes” votes from the shareholders to be
successfully elected.
New Problematic Director
Appointment
Indicator variable equals one if the firm has newly appointed at least
one problematic independent director, and zero otherwise.
Number of Board Meetings Number of board meetings held by the firm during the fiscal year.
Old Firm Indicator variable equals to one if the firm's age is greater than the
median firm age, and zero otherwise.
Pre-SOX Indicator variable equals one if the observation occurs in the fiscal year
2002 and before, and zero otherwise.
Poor Tobin's Q An indicator variable equals to one if the firm’s Tobin’s Q is below the
bottom quartile of all firms during that year, and zero otherwise.
Proportion Problematic Director The proportion of problematic directors among the independent
directors of the board.
Proportion PID on Audit
Committee
Proportion of problematic independent directors on the audit
committee.
Proportion PID on Compensation
Committee
Proportion of problematic independent directors on the firm’s
compensation committee.
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Proportion PID on Nomination
Committee
Proportion of problematic independent directors on the nomination
committee.
Renomination of Problematic
Director
An indicator variable that equals to one if the firm has renominated
problematic directors during the year and zero otherwise.
ROA Earnings before interest, taxes, depreciation and
amortization/beginning-year total assets.
Sales Growth Ln(1 + sale/beginning-year sale).
Staggered Board An indicator variable equals to one if only part of the directors on the
board are elected each year, and zero otherwise.
Tangibility Total gross property, plant and equipment/beginning-year total assets.
Tobin’s Q (Total assets - book value of equity + market value of equity) /
beginning-year total assets.
Total Assets Book value of beginning-year total assets in millions of dollars.
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Appendix B: The Mutual Fund Votes Sample in Table 2
We examine how mutual fund investors vote when they are distracted in Table 2. Our initial mutual fund
investors sample is drawn from the CRSP survival bias free mutual fund database. Following previously studies
including Kacperczyk, Sialm, and Zheng (2008) and Dimmock, Gerken, Ivkovic, and Weisbenner (2016), we
focus on actively-managed domestic equity funds and eliminate balanced, bond, international, money market, and
sector funds. We also remove funds that hold less than 10 stocks and have less than two million total net assets.28
We then merge the mutual fund holding data with ISS Voting Analytics database using fund and fund
family names. Only since 2003, mutual funds are required to disclose their votes through N-PX filings to the
Securities and Exchange Commission (SEC). Therefore, our mutual fund voting data is only available from 2003
onwards.
Our dataset contains information on the number of votes casted by each mutual fund investor for each of
the directors up for election during the annual general meeting. For each fund vote, we can observe whether the
mutual fund shareholder vote “For,” “Against,” or “Withhold” the vote for each director election proposal in the
investee company’s annual meeting.
To obtain information on director classification and characteristics, we further restrict our mutual fund
vote sample to votes for director elections. We match companies from ISS Voting Analytics to RiskMetrics using
CUSIP, ticker, and company names. Then, we extract director names from the item description in ISS Voting
Analytics, and match them to the director names from the same company in the RiskMetrics director database.
We manually verify these company and director matches. With these procedures, we are able to match 98%
director election proposals from ISS Voting Analytics to RiskMetrics.
28 Following previous studies, we identify the type of fund by Lipper classification, which becomes populated
since 1998. For example, we identify actively-managed US equity funds with objective code "G," "GI," "LSE,"
or "SG," or the classification code "LCCE," "LCGE," "LCVE," "LSE," "MCCE," "MCGE," "MCVE," "MLCE,"
"MLGE," "MLVE," "SCCE," "SCGE," or "SCVE." To further exclude index funds, we manually checked the
fund names to further exclude index funds.