Investment Duration and Corporate Governance

Investment Duration and Corporate Governance*

Youngjoo Lee Sogang University

Kee H. Chung**

State University of New York at Buffalo and Chung-Ang University

___________________________________________

*Acknowledgements: This work was supported by the Sogang University Research Grant 201210050.01. The authors thank Daisy Chung, Kenneth Kim, Alexandra Niessen, Jhinyoung Shin, Cristian Tiu, Sean Yang, Woongsun Yoo, and seminar participants at SUNY-Buffalo and session participants at the Financial Management Association (FMA) conference and the Ninth Annual Conference on Asia-Pacific Financial Markets (CAFM) for their valuable comments and suggestions. Earlier versions of this paper were circulated under the title “Shareholder Activism and Corporate Governance: The Role of Institutional Investors.” The usual disclaimer applies.**Corresponding Author: Kee H. Chung, Louis M. Jacobs Professor, Department of Finance and Managerial Economics, School of Management, State University of New York (SUNY) at Buffalo, Buffalo, NY 14260. Tel.: 716-645-3262; Fax: 716-645-3823; E-mail: [email protected].

Investment Duration and Corporate Governance

Abstract

In this study we analyze the relation between institutional investment duration and corporate governance using a new metric of investment duration that accounts for firm-specific investment durations of each institution. We conjecture that institutional investors that hold a firm’s shares for a longer duration have greater incentives and ability to influence the firm’s governance structure. Consistent with this conjecture, we find that a broadly defined index of corporate governance increases with the duration of institutional ownership. We also show that the relation between investment duration and corporate governance varies across different types of institutions and across firms with different stock market liquidities.

Keywords: Corporate governance; Institutional investors; Investment duration; Monitoring incentive; Shareholder activism

JEL: G20, G34

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1. Introduction

The role of institutional investors in various financial interactions has received

increasing attention from both public media and academia as the level of institutional

ownership in U.S. corporations has increased dramatically during the last two decades.1 In

this study we investigate institutional shareholder activism by analyzing the relation

between institutional investment duration (INVDUR) and a broadly defined index of

corporate governance (CGINDEX).2 The extent to which institutional investors can

influence a firm’s governance structure is likely to depend on how long they have held the

firm’s shares because investment duration affects their incentives and abilities to influence

corporate governance. Institutional investors with short investment duration have little

incentive to spend resources on corporate governance because they are not likely to remain

shareholders and capture future benefits. In addition, they have less time to learn about the

firm and thus are less able to interfere with the firm’s management due to the lack of

expertise and knowledge.

Many institutions index a large portion of their portfolio. For example, Carleton et

al. (1998) find that TIAA-CREF indexes 80% of its domestic equity portfolio. Large

ownership and indexing strategy provide institutional investors with incentives to interfere

with management and pursue activist agenda because they cannot simply vote with their

feet. Prior research finds evidence that institutional efforts to improve corporate governance

and/or firm performance pay off because they bring benefits to shareholders. For instance,

1 The Conference Board reports that institutional ownership in the largest 1,000 U.S. corporations increased from 46.6% in 1987, to 61.4% in 2000, and then to 73% by the end of 2009.2 Instead of engaging in shareholder activism, institutional investors may vote with their feet (i.e., sell shares) when they are dissatisfied with a firm’s management. For example, Parrino et al. (2003) show that aggregate institutional ownership and the number of institutional investors decline in the year prior to forced CEO turnover.

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Brav et al. (2008) find that Schedule 13D filings by the hedge fund with activist agenda are

associated with positive abnormal stock returns.3 Klein and Zur (2009) also find that firms

targeted by activist institutional investors exhibit positive abnormal stock returns around

the initial Schedule 13D filing date and over subsequent periods.4

Our study contributes to a growing literature that analyzes various ramifications of

investment duration for corporate decisions and market valuation. Gaspar et al. (2005) find

that firms held by short-term investors have a weaker bargaining position in acquisitions.

Yan and Zhang (2009) analyze the relation between institutional trading and future earnings

surprises and find that short-term institutions are better informed than long-term

institutions. Cella et al. (2013) show that institutional investors with short trading horizons

magnify the impact of market-wide negative shocks on share price. Derrien et al. (2013)

hold that longer investor horizons attenuate the effect of stock mispricing on various

corporate policies.5 Gaspar et al. (2013) examine how shareholder investment horizons

influence payout policy choices and show that firms held by short-term investors make

repurchases more often because they care mostly about the short-term price reaction.

Harford et al. (2013) show that firms with longer investor horizons hold more cash and are

more likely to invest in projects with long-term payoffs.

Despite the different roles of long- and short-term institutional investors in

shareholder activism and their potential impact on corporate governance, prior research

3 Investors are required to file Schedule 13D with the SEC within 10 days of transaction after they acquires more than 5% of any class of a company’s shares.4 Han et al. (2014) find evidence that good corporate governance helps protect shareholder value by mitigating information asymmetries between managers and shareholders. Kim, Lee, and Yang (2013) show that firms with a greater level of governance transparency have a higher firm value.5 Derrien et al. (2013) show that when a firm is undervalued, greater long-term investor ownership is associated with more investment, more equity financing, and less payouts to shareholders.

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provides limited evidence on the issue. Chen et al. (2007) conjecture that only independent

institutions with long-term investments make efforts to monitor and influence managers.6 In

support of this conjecture, they show that only concentrated holdings by independent long-

term institutions are related to post-merger performance and the presence of these

institutions increases the probability of bad bid withdrawals. Attig et al. (2012) show that

the sensitivity of corporate investment outlays to internal cash flows is lower with the

presence of long-term institutional investors and interpret this result as evidence that long-

term institutional investors have greater incentives to monitor managers. In a similar vein,

Attig et al. (2013) show that the cost of equity decreases with the presence of long-term

institutional investors. We extend the literature of investment duration (or horizon) by

analyzing the impact of institutional investment duration on corporate governance.

Previous studies (e.g., Bushee 1998; Gaspar et al. 2005) determine whether an

institution is a long- or short-term investor based on the average turnover ratio or holding

period of its entire portfolio of stocks. This method could be problematic because it

considers an institution a short-term investor if its average turnover ratio is high although

its turnover ratios for some stocks could be quite low. Generally, institutional investors

hold a large number of stocks, and their investment strategies and holding periods vary

considerably across stocks in their portfolio. An institution may be actively involved with a

firm’s management and governance as a long-term investor, but may be a passive investor

with short investment horizons in other firms. The present study analyzes the effect of

investment duration on corporate governance using a new metric that accounts for firm-

6 Chen et al. (2007) define long-term institutions as those institutions that hold a firm’s shares for more than one year.

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specific investment durations of each institution. Specifically, we measure the mean

institutional holding period for each firm across all institutions that hold its shares (instead

of the mean holding period of each institutional investor for all stocks in its portfolio) and

use it in our empirical analysis.

Our study differs from prior research also in that we employ a comprehensive

measure of corporate governance. Many prior studies focus on whether institutional

investors exert an influence on a single dimension of corporate governance, such as CEO

compensation, CEO turnover, or antitakeover practices.7 For example, Hartzell and Starks

(2003) and Almazan et al. (2005) examine whether institutional ownership concentration is

related to the pay-for-performance sensitivity and the level of CEO compensation. Huson et

al. (2001) analyze the relation between CEO turnover and institutional ownership. Bizjak

and Marquette (1998) study shareholder proposals to rescind poison pills.

Shareholder proposals submitted by institutional investors usually cover a wide

range of corporate governance issues. For example, Campbell et al. (1999) find that the

shareholder proposals in their study sample cover 17 corporate governance related issues,

including classified board, executive compensation, cumulative voting, sale of the

company, poison pill, and board independence. Other studies (e.g., John and Klein 1995;

Wahal 1996; Del Guercio and Hawkins 1999; Gillan and Starks 2000) report similar

findings. 8 To reflect that institutional shareholder activism may affect multiple dimensions

of corporate governance, our study considers 50 governance standards that encompass the

7 Although Chung and Zhang (2011) use a comprehensive measure of corporate governance, the main focus of their study is whether institutional investors are attracted to firms with better governance provisions.8 Gillan and Starks (2000) show that shareholder proposals sponsored by institutions or coordinated groups receive substantially more support than those sponsored by individuals and that the stock market reaction varies with sponsor identity.

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following seven categories: board, audit, charter/bylaws, state of incorporation, executive

and director ownership, executive and director compensation, and progressive practices.

Prior research suggests that only certain types of institutional investors may play the

role as an active monitor.9 For example, Almazan et al. (2005) find that the pay-for-

performance sensitivity is positively related to the ownership concentration of independent

investment advisors and investment companies, and insignificantly related to that of bank

trusts and insurance companies. They note that independent investment advisors and

investment companies may have lower monitoring costs than bank trusts and insurance

companies because the former group has better employee skills and ability to collect

information, faces less regulatory restrictions, and make less business ties with

corporations. Woidtke (2002) analyzes the valuation effects of public and private pension

funds and reports that firm value is positively related to ownership by private pension funds

and negatively related to ownership by public pension funds. The present study examines

whether the relation between corporate governance and investment duration varies across

different types of institutions. In this respect, our study complements prior research that

focuses on shareholder activism by a particular institutional investor, such as the California

Public Employees Retirement System (CalPERS) or TIAA-CREF.10

9 Not all institutional investors may engage in shareholder activism since they differ in terms of their trading styles, incentives for managers, clienteles, legal and regulatory environments, and ability to gather and process information (Gillan and Starks 2000). Although institutional investors do not run a company, they can influence the board of directors and management through various channels and means (e.g., dialogue with management to voice their concerns on a particular issue; litigation; or formal proposals to be voted on at a shareholders’ meeting). Their goal is to bring about changes in corporate policy and, in extreme cases, the management itself. 10 See Nesbitt (1994), Smith (1996), Wu (2004), and Barber (2006) for CalPERS and Carleton et al. (1998) for TIAA-CREF.

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We show that CGINDEX increases with the duration of institutional ownership

(INVDUR), suggesting that institutional investors that hold a firm’s shares for a longer

period have greater incentives and abilities to influence the firm’s governance structure.

The relation between INVDUR and CGINDEX varies across different types of institutions

and the relation is particularly strong for public pension funds. We show that the presence

of large institutional investors with a long investment horizon increases the likelihood of a

firm’s adoption of the best governance standards that are related to audit, board structure,

executive and director compensation, and progressive practices. In contrast, the presence of

long-term institutional investors does not have an impact on the governance practices

related to either anti-takeover or executive and director ownership structure. Finally, we

find that longer INVDUR is more effective in improving the governance structure of firms

with higher levels of stock market liquidity. We interpret this result as evidence that firms

have greater incentives to improve their governance structure to retain long-term

institutions, especially when the threat of exit is greater.

Our study contributes to the literature in several important dimensions. First, our

study underscores the importance of the role of investment horizon in shareholder activism

using a newly developed measure of institutional investment duration. Second, in contrast

to prior research, we analyze the effect of institutional shareholder activism on a broadly

defined index of corporate governance and show that institutional shareholder activism

affects multiple dimensions of corporate governance. Finally, we shed further light on

whether or not shareholder activism varies across different types of institutional investors

and across firms with different levels of stock market liquidity.

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The remainder of the paper is organized as follows. Section 2 explains our data

sources and variable measurement methods. Sections 3 through 6 present empirical results.

Section 7 concludes the paper.

2. Data sources, variable measurement methods, and descriptive statistics

Our sample comprises publicly traded U.S. companies during the nine-year period

from 2001 through 2009. The sample period starts from 2001 because the Institutional

Shareholder Services (ISS) provides corporate governance data from that year. We obtain

financial and stock return data from Standard & Poor’s Compustat and the Center for

Research in Securities Prices (CRSP). We obtain institutional ownership data from

Thomson Reuters’ Institutional (13F) Holdings. Following prior research, we exclude

financial firms (SIC code from 6000 to 6999) and utility firms (SIC code from 4900 to

4949) from the study sample. We winsorize the variables at the 1% and 99% levels to

minimize the effect of outliers. The final sample consists of 19,204 firm-year observations.

2.1. Corporate governance index

The ISS data contain more than 60 governance provisions in the following eight

categories: board, audit, charter/bylaws, state of incorporation, executive and director

ownership, executive and director compensation, progressive practices, and director

education. We construct our yearly corporate governance index using 50 governance

provisions in seven categories, including 17 provisions from board, four provisions from

audit, eight provisions from charter/bylaws, ten provisions from compensation, four

provisions from ownership, six provisions from progressive practices, and one provision

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from state of incorporation.11 Appendix I provides the list of these governance provisions.

We determine whether a particular governance standard is met using the minimum standard

provided in ISS Corporate Governance: Best Practices User Guide and Glossary (2008).

Following prior studies, we create a governance index (CGINDEX) for each firm by

awarding one point for each governance provision that satisfies the ISS standards.12 ISS

collects data from proxy statements, which contain information on the firm’s governance

characteristics for the preceding year (Ciceksever et al. 2006). To account for the time lag

in the ISS data, we assume that CGINDEX obtained from the ISS data in year t reflects the

governance quality in year t-1 in our empirical analysis. For instance, CGINDEX obtained

from the 2005 ISS data is considered CGINDEX in 2004.

2.2. Institutional investment duration (INVDUR)

Generally, institutional investors hold a large number of stocks and their

investment strategies and lengths of investment duration vary across stocks. An institution

could be actively involved with a firm’s management and governance as a long-term

investor, but may be a passive investor with a short investment horizon in other firms.

Hence, classifying an institution into a short- or long-term investor in its entirety is

problematic. To avoid this problem, we first measure an institution’s investment duration

for each stock in its portfolio separately and then determine whether a stock is held by long-

or short-term institutional investors based on the mean investment duration across all

institutions that hold the stock.

11 We exclude governance provisions in the category of director education. ISS recommends board members to attend “ISS-accredited” director education program. 12 See, for example, Chung et al. (2010) and Chung and Zhang (2011).

9

To determine the investment duration of institution k in stock i, we first identify the

first quarter in which institution k reported its shareholding in firm i from the 13F data

provided by Thomson Reuters. We then measure institution k’s investment duration for firm

i at the end of year t, INVDURkit, by the number of quarters between the first quarter and

the last quarter of year t.

To shed some light on the extent to which an institution’s investment duration

differs across stocks in its portfolio, we classify stocks in each institution’s portfolio into

six different investment duration categories (0-1 year, 1-2 years, 2-3 years, 3-4 years, 4-5

years, and above 5 years) and then calculate the proportion of stocks that belong to each

category. Rows 1 through 7 in Table 1 show the mean proportion of stocks in each category

for each type of institutions and Rows 8 shows the mean proportion across all institutions.

The results show that public (private) pension funds hold 33% (32%) of stocks in their

portfolios for more than five years and 24% (29%) of stocks for less than one year. In

contrast, hedge funds hold 5% of stocks for more than five years and 62% of stocks in their

portfolios for less than one year. On average, 12% of our sample stocks are held by

institutional investors for more than five years and 48% of them are held by institutional

investors for less than one year. These results indicate that regardless of type, the

investment duration of an institutional investor varies significantly across stocks in its

portfolio and thus classifying an institution into a long- or short-term investor based on its

average investment duration across all stocks it holds could be quite misleading.

[Place Table 1 around here]

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We measure the institutional investment duration of stock i in year t, INVDUR it, by

the weighted mean value of the investment duration of all institutions that hold stock i at

the end of year t: INVDURit = Σ[wkit x log(INVDURkit)], where wkit is the fraction of firm i’s

total institutional ownership held by institution k at the end of year t and Σ denotes the

summation over k.13 We use the logarithm of INVDURkit because its distribution is highly

skewed.

2.3. Control variables

Institutions are likely to be effective in shareholder activism when their ownership

is concentrated (Shleifer and Vishny, 1986). We measure institutional ownership

concentration (CONCENTRATION) by the Herfindahl index and use it as a control

variable. The Herfindahl index of firm i in year t is defined as Hit = 100 ∑Skt2, where Skt is

the fraction of firm i’s shares held by institution k in year t and ∑ denotes summation over

k. We expect a firm with more concentrated institutional ownership (i.e., a greater

Herfindahl index) to have a higher governance index. Institutions are also likely to be more

effective in shareholder activism in a given firm when they hold a larger fraction of the

firm’s shares. Hence we use the total ownership of institutional investors (IO) for each firm

as a control variable.

Prior research shows that corporate governance is related to a number of firm

attributes. Dey (2008) employs various firm characteristics–organizational complexity,

size, volatility in operating environment, ownership structure, leverage, and free cash flow–

as proxies for agency conflicts and shows that firms with greater agency conflicts have 13 We also analyze the relation between investment duration and corporate governance using the simple (i.e., unweighted) average investment duration of all institutions and find qualitatively similar results.

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better governance mechanisms in place. Ciceksever et al. (2006) employ firm size,

investment opportunity, intangible assets, and income volatility as proxies for monitoring

costs and show that companies with larger monitoring costs exhibit better governance

structure. Similarly, Linck et al. (2008) view firm complexity and monitoring costs as

determinants of corporate governance. They use firm size, debt ratio, and the number of

business segments as proxies for firm complexity and the market-to-book ratio, R&D

spending, and return volatility as proxies for monitoring costs. Klapper and Love (2004)

show that corporate governance structure is significantly related to firm size, sales growth

rate, and capital intensity.

In our empirical analysis, we include firm size, R&D expenditure, volatility in

operating profit, market-to-book ratio, leverage, free cash flow, firm age, and stock returns

as control variables. Firm size (FSIZE) is measured by the logarithm of total assets, R&D

expenditure is scaled by total assets, volatility in operating profit (VOLATILITY) is

measured by the standard deviation of operating profit in the past five years, market-to-

book ratio (MTB) is measured by the ratio of the summation of the market value of equity

and long-term debt to total assets, and leverage ratio (LEVERAGE) is measured by the

ratio of long-term debt to total assets. Similar to Dey (2008), we measure free cash flow

(FCF) by the difference between operating cash flow and capital expenditure scaled by total

assets. Stock return (RET) is the buy-and-hold stock returns over the past five years.

Finally, we include firm age (FIRMAGE) as an additional control variable because

firm age is likely to be correlated with both corporate governance and institutional

investment duration. For example, Gillan et al. (2006) find that older firms are more likely

to adopt antitakeover amendments. The correlation between firm age and institutional

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investment duration can arise because institutional investors are likely to purchase shares of

older firms earlier than younger firms. We measure firm age by the number of years since

the firm first appeared in the CRSP database.

2.4. Descriptive statistics and correlation matrix

We present descriptive statistics and the correlation matrix of the variables in Table

2. Panel A shows that CGINDEX ranges from 1 to 42, with the mean (median) value of

24.4. (25). The mean (median) value of INVDUR is 2.5 (2.57) and the mean (median) value

of institutions’ aggregate ownership is 46.9% (49.1%). Panel B shows that CGINDEX is

positively correlated with INVDUR. CGINDEX is also positively correlated with

institutional ownership concentration (CONCENTRATION), aggregate institutional

ownership (IO), firm size (FSIZE), free cash flow (FCF), and firm age (FIRMAGE), and

negatively correlated with R&D expenditures, volatility (VOLATILITY), market to book

ratio (MTB), leverage (LEVERAGE), and past stock returns (RET).


3. Empirical results

3.1. Regression results using the level variables

We estimate the following regression model to examine the relation between

CGINDEX and INVDUR after controlling for the effects of other variables (see Appendix

II for the definition of each variable):

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CGINDEX¿=β0+β1 INVDUR¿−1+β2 CONCENTRATION¿−1(¿ IO¿¿¿−1)+ β3 FSIZE¿−1+β4 R∧D¿−1+β5VOLATILITY ¿−1+β6 MTB¿−1+β7 LEVERAGE¿−1+β8 FCF¿−1+β9 FIRMAGE¿−1+β10 RET ¿−1 +ε ¿¿. (1)

We use lagged values of independent variables to mitigate a potential reverse causality

problem.

We estimate regression model (1) using the ordinary least squares (OLS) method

with standard errors clustered by firm and year in order to address the possible biases in the

standard errors in the presence of cross-sectional and time-series dependence (Petersen

2009). The first column in Table 3 shows the results when we include institutional

ownership concentration (CONCENTRATION) and the second column shows the results

when we include institutional ownership (IO) in the regression.14 The estimated

coefficients on INVDUR are positive and significant at the 1% level, indicating that

companies that are held by institutions with a longer investment horizon exhibit a higher

CGINDEX. The coefficient on CONCENTRATION (IO) is also positive and significant at

the 1% level, suggesting that institutional investors exercise a greater influence on

corporate governance when their ownership is concentrated (large). We interpret these

results as evidence that institutional investors’ monitoring incentives and abilities increase

with both their investment duration and ownership concentration (size).

The results for the other control variables are generally in line with those reported in

previous studies. For example, we find that CGINDEX is positively related to firm size,

R&D expenditures, operating profit volatility, and firm age, and negatively related to

market-to-book ratio, leverage, free cash flow, and past stock returns.

14 We do not include both variables in the same regression because they are highly correlated.

14


3.2. Regression results using changes in the variables

Regression models using changes in the variables are less likely to suffer from

econometric problems (e.g., nonstationarity) than those using the level variables. As a

robustness check, we examine whether changes in CGINDEX can be explained by changes

in INVDUR. To account for the possibility that changes in CGINDEX and INVDUR may

occur gradually and test the hypothesized direction of causality, we regress changes in

CGINDEX between year t and year t-2 on changes in INVDUR and control variables

between year t-1 and year t-3. The results (see Panel A in Table 4) show that the

coefficients on changes in INVDUR are positive and significant, providing further evidence

that long-term institutional investors play a greater role in corporate governance than do

short-term institutional investors. The regression coefficients on changes in

CONCENTRATION and IO are both positive, but only the coefficient on IO is statistically

significant.

To further assess the robustness of the relation between institutional investment

duration and CGINDEX, we classify an institution as a long-term (short-term) institution if

its length of investment in a firm is longer (shorter) than two years and calculate the total

ownership of long-term institutions (IO_LONG) and the total ownership of short-term

institutions (IO_SHORT) for each firm. Similarly, we count the number of long-term

institutions (NOINST_LONG) and the number of short-term institutions

(NOINST_SHORT) for each firm. The first column in Panel B of Table 4 shows the results

when we include changes in the total ownership of long-term institutions (∆IO_LONG) and

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changes in the total ownership of short-term institutions (∆IO_SHORT) in the regression.15

Similarly, the second column shows the results when we include changes in the number of

long-term institutions (∆NOINST_LONG) and changes in the number of short-term

institutions (∆NOINST_SHORT) in the regression. As in Panel A, we regress changes in

CGINDEX between year t and year t-2 on changes in independent variables between year t-

1 and year t-3.

We find that the coefficient on ∆IO_LONG (∆NOINST_LONG) is positive and

significant at the 1% level, suggesting that an increase in the ownership (number) of long-

term institutions in a firm is associated with an improvement in the firm’s governance

structure. In contrast, we find that the coefficient on ∆IO_SHORT is not significantly

different from zero and the coefficient ∆NOINST_SHORT is significantly negative. These

results suggest that only long-term institutions exert a positive impact on CGINDEX.


3.3. Regression results by governance categories

In the previous sections, we established a positive relation between the broadly

defined index of corporate governance and the investment duration of institutional

investors. In this section we shed further light on the effect of institutional investment on

corporate governance by examining which specific governance categories are related to

institutional investment duration. Shareholder activism is a costly endeavor with uncertain

outcomes for institutional investors. Consequently, institutional investors may put more

15 We do not include ∆CONCENTRATION in this regression for the same reason explained earlier.

16

effort into select governance features that they consider most important for improving firm

performance.

To determine which governance categories are related to institutional investment

duration, we regress CGINDEX for each one of the six governance categories in the ISS

database on the same set of explanatory and control variables that are included in regression

model (1).16 The results (see Table 5) show that the coefficients on INVDUR are positive

and significant in the regression model for each of the following governance categories:

audit, board, compensation, progressive practices, regardless of whether we include either

CONCENTRATION or IO in the model. These results indicate that the presence of

institutional investors with a long-term investment horizon increases the likelihood of a

firm’s adoption of the best governance standards in these categories. In contrast, the

presence of long-term institutional investors does not have an impact on the governance

practices related to either anti-takeover or executive and director ownership structure.

The coefficients on CONCENTRATION and IO are generally consistent with prior

empirical findings. Gillan et al. (2006) find that companies with higher institutional

ownership have more powerful boards and more antitakeover provisions. Similarly, we find

that the coefficients on CONCENTRATION and IO are positive in the regression model for

BOARD and negative in the regression model for CHATERS/BYLAWS.17 Johnson and

Shackell (1997) show that a company is less likely to receive shareholder proposals on

executive compensation when institutions hold a larger fraction of its shares. In contrast,

we find that executive and director compensation is insignificantly related to

16 State of incorporate category is excluded because it contains only one governance provision. 17 Note that firms with larger scores of CHATERS/BYLAWS in our study have smaller and/or weaker antitakeover provisions.

17

CONCENTRATION and IO, but significantly related to INVDUR, suggesting that long-

term institutional investors are more interested in executive and director compensation

scheme than are short-term institutional investors.


4. Corporate governance and investment duration by the type of institutions

In this section we examine whether the relation between corporate governance and

institutional investment duration varies across the seven types of institutions: public

pension funds, private pension funds, hedge funds, bank trusts, insurance companies,

investment companies, and investment advisors. Both anecdotal evidence and academic

research indicate that pension funds are amongst the most active investors in the U.S.

Gillan and Starks (2000) show that institutional investors submitted 463 proxy proposals

between 1987 and 1994 and the majority of these proposals were sponsored by pension

funds. Although the proxy proposals submitted by pension funds have declined

significantly since the early 1990s, pension funds have been most vocal in calling for

corporate governance reforms through direct negotiation with corporate management

and/or public targeting. Brav et al. (2008) investigate hedge funds’ activism (through

Schedule 13D filing) and find increases in target firms’ dividend payout, operating

performance, and CEO turnover. Almazan et al. (2005) categorize bank trusts and

insurance companies as passive investors and independent investment advisors and

investment companies as active investors and find that only investment advisors and

investment companies exert influences on executive compensation.

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To examine whether the effect of institutional investment duration on corporate

governance varies with the type of institutions, we conduct regression analysis for each

type of institutions and report the results in Table 6. The first three columns show the

results when we include the investment duration (INVDUR_TYPE) of public pension

funds, private pension funds, or hedge funds as an explanatory variable in the regression

model. [Appendix III shows the list of public and private pension funds.] The next four

columns show the results when we include the investment duration of bank trusts, insurance

companies, investment companies, or investment advisors as an explanatory variable. In

each of these regressions, we also include the investment duration of all other types of

institutional investors (INVDUR_OTHER TYPE). Hence, for example, we include both the

investment duration of public pension funds and the investment duration of all other

institutional investors in the regression model for public pension funds. Similarly, we

include both the ownership of each type of institutional investors (IO_TYPE) and the total

ownership of all other institutional investors (IO_OTHER TYPE) in the regression model

for each type of institutional investors to assess the effect of ownership level on corporate

governance.

The results show that the coefficients on the investment duration of public pension

funds, hedge funds, bank trusts, insurance companies, investment companies, and

investment advisors are all positive and significant at the 1% level. The coefficient on the

investment duration of private pension fund is positive but insignificant. These results

suggest that institutions with a longer investment horizon exert greater influences on

corporate governance regardless of their type (except private pension funds).

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Comparison of the regression coefficients on investment duration across different

types of institutions indicates that the relation between CGINDEX and INVDUR is

strongest for public pension funds, followed by insurance companies, banks, and

investment advisors. These results suggest that how investment duration affects corporate

governance varies across different types of institutions, reflecting their differential

incentives and abilities to influence corporate governance. In particular, the large and

highly significant coefficients on investment duration for public pension funds are

consistent with both anecdotal evidence and the finding of prior research that public

pension funds are amongst the most active investors in the U.S. Not surprisingly, the

coefficients on INVDUR_OTHER TYPE are all positive and significant and tend to be

smaller when the coefficients on INVDUR_TYPE are larger across different types of

institutional investors.

The effect of institutional ownership (IO) on the governance index varies

significantly across different types of institutions. For example, the coefficients on

IO_TYPE are negative and significant for pension funds and insurance companies, but

positive and significant for hedge funds and banks, indicating that greater ownership by

pension funds and insurance companies does not necessarily imply better corporate

governance. Finally, the coefficients on IO_OTHER TYPE are all positive and significant

across all types of institutions. This result indicates that although the effect of ownership

size on CGINDEX varies significantly across different types of institutions, they exert in

aggregate a positive impact on CGINDEX.


20

5. Effect of liquidity on the relation between investment duration and corporate

governance

Institutional investors’ incentives to engage in shareholder activism are likely to

depend on the benefit and cost associated with the activism. We conjecture that the benefit

and cost associated with shareholder activism vary with the stock market liquidity of the

firm’s shares. If the liquidity of the firm’s shares is high, institutional investors can easily

exit (i.e., sell the firm’s shares) when they are not satisfied with the firm’s management.

Hence, higher liquidity may imply lower shareholder activism by institutional investors

(Bhide 1993), which may adversely affect corporate governance. Conversely, higher

liquidity may be associated with better governance structures if the threat of exit is more

effective for firms with the higher stock market liquidity of their shares. Managers of such

firms may make greater endeavor to improve governance structure in an effort to prevent

institutional investors from exit, which may adversely affect share price. These

considerations suggest that the effect of liquidity on corporate governance is likely an

empirical question.

We measure the liquidity of the firm’s shares by the proportional bid-ask spread

using data from the CRSP database.18 Prior research (e.g., Bessembinder 2003) uses the

bid-ask spread to perform inter-market comparisons of trading costs. In addition, regulators

enact various market reforms to reduce the cost of trading and assess the effectiveness of

18 Chung and Zhang (2014) show that the CRSP-based spread is highly correlated with the TAQ-based spread using data from 1993 through 2009: the annual average of monthly cross-sectional correlation coefficients between the CRSP spread and the TAQ spread ranges from 0.8267 to 0.9603 for NYSE/AMEX stocks and from 0.9193 to 0.9729 for NASDAQ stocks.

21

these reforms by analyzing their impact on the bid-ask spread.19 We calculate the bid-ask

spread of stock i on day τ using the following formula: SPREADiτ = (Askiτ – Bidiτ)/Miτ;

where Askiτ is the ask price of stock i on day τ, Bid iτ is the bid price of stock i on day τ, and

Miτ is the mean of Askiτ and Bidiτ. For each stock, we then calculate the average spread

during each year from 2000 through 2008. We include both the spread and the interaction

variable between the spread and institutional investment duration in the regression model.

The results (see Table 7) show that the coefficients on the interaction variable are

negative and significant, regardless of whether we include either COCENTRATION or IO

in the model, indicating that the positive effect of investment duration on CGINDEX

decreases with the spread.20 Put differently, longer institutional investor duration is more

effective in improving a firm’s governance structure when the stock market liquidity of the

firm is higher. These results are consistent with the notion that when institutional investors

can exit more easily, firms are more inclined to improve governance structure to avoid their

exit. Table 7 also shows that the coefficients on the spread are negative and significant,

which is consistent with the finding of prior research (see Chung et al. 2010).


6. Robustness check using alternative measures of institutional investment duration

19 For instance, the U.S. Securities and Exchange Commission (SEC) enacted the Limit Order Display Rule to reduce the bid-ask spread of NASDAQ-listed stocks.20 We find qualitatively similar results when we use the illiquidity measure of Amihud (2002) instead of the bid-ask spread. The coefficients on the interaction term between the Amihud measure and institutional investment duration are negative and significant regardless of whether we include either COCENTRATION or IO in the model.

22

In this section we use alternative measures of institutional investment duration to

assess the robustness of our results. Elyasiani and Jia (2008) employ the persistency of

institutional ownership, the non-zero-points duration, and the maintain-stake-points

duration to investigate the monitoring effect of long-term institutional investors on firm

performance. Following their study, we first calculate the mean and standard deviation of

institution k’s ownership in firm i over the past 20 quarters. We use the ratio of the mean of

the ownership to the standard deviation over the past 20 quarters as institution k’s

ownership persistency in firm i at time t (IOPkit). We then measure firm i’s institutional

ownership persistency at time t by IOP¿=∑N =1

N ¿ IOPkit

N ¿, where Nit is the number of institutions

which own firm i’s shares at time t.

The non-zero-points duration is the number of quarters during which institution k

holds non-zero shares over the past 20 quarters. The maintain-stake-points duration is the

number of quarters during which institution k increases or maintains the ownership stake

over the past 20 quarters. For the firm-level duration, both duration measures are averaged

across all institutions in the firm’s ownership structure.

Table 8 shows the regression results using these alternative institutional duration

measures. The first two columns show the results when we measure institutional investment

duration with IOP, the next two columns show the results with the non-zero-points

duration, and the last two columns show the results with the maintain-stake-points duration.

The results show that the coefficients on these institutional duration measures are positive

in all six regressions and statistically significant in most regressions (five out of six cases).

23

These results suggest that CGINDEX increases with the stable and long-term existence of

institutional investors, which is consistent with our main results presented above.


7. Summary and concluding remarks

Corporate ownership structure in the U.S. has gone through a major transformation

during the last half-century. In particular, corporate ownership has become much more

concentrated in the hands of institutional investors. Consequently, while corporate

managers once faced a dispersed and relatively powerless crowd of shareholders, they now

have to deal with an increasingly powerful group of institutional investors. Moreover,

institutional investors have expanded the domain of their activism from standard

shareholder rights to issues of how chief executive officers are chosen, how much

executives are paid, and how the board is made up and structured.

Not surprisingly, researchers have paid increasing attention to institutional

investors’ roles in the financial market, such as the effects of institutional ownership on

firm value, analyst following, stock returns, and corporate governance. In particular, a large

number of studies have examined whether and how institutional investors proactively work

in partnership with companies to improve corporate governance structure. Some prior

research focuses on shareholder activism by a particular institutional investor (such as

CalPERS or TIAA-CREF) and other studies analyze the relation between the total

institutional ownership of a firm and a specific aspect of its governance structure. In our

study, we shed further light on the role of institutional investors in corporate governance by

24

analyzing the effect of institutional investment duration on the broadly constructed index of

corporate governance as well as on specific governance provisions.

Our results suggest that institutional influence on a firm’s governance practices

depends on how long they have held the firm’s shares. The results are consistent with our

conjecture that institutional investors with a shorter investment horizon would be less

interested in spending resources on corporate governance because they are less likely to be

the recipients of the resultant benefits. The long-term presence of institutional investors

increases the likelihood of a firm’s adoption of governance standards that are related to

audit, board structure, executive and director compensation, and progressive practices,

suggesting that institutional investors’ interest covers a broad range of corporate

governance practices.

We also show that the relation between investment duration and corporate

governance varies materially across different types of institutions, reflecting their

differential incentives and abilities to influence corporate governance, The effect of

investment duration on corporate governance is particularly strong for public pension

funds, which is consistent with the finding of prior research that pension funds are amongst

the most active investors in the U.S. We also find evidence that longer institutional investor

duration is more effective in improving corporate governance structure for firms with

higher stock market liquidity.

25

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29

Appendix I 50 governance provisions used in the construction of the corporate governance index

Provision Governance StandardAuditAudit committee composition Audit committee of the board should be composed

solely of independent directors.Audit fees Consulting fees (audit-related and other) should be less

than audit fees.Audit ratification Shareholders should be permitted to ratify

management’s selection of auditors each year.Audit rotation The company should disclose its policy with respect to

the rotation of auditors.BoardBoard composition At least a majority of the directors on the board should

be independent.Nominating committee composition Nominating committee of the board should be

composed solely of independent directors.Compensation committee composition Compensation committee of the board should be

composed solely of independent directors.Governance committee composition The functions of a governance committee should be

handled by a committee of the board, typically the nominating or the governance committee.

Board structure Directors should be accountable to shareholders on an annual basis.

Board size Boards should not have fewer than 6 members or more than 15 members.

Change in board size Shareholders should have the right to vote on changes to expand or contract size of the board.

Cumulative voting Shareholders should have the right to cumulate their votes for directors.

Board served on by the CEO The CEO should not serve on more than two other boards of public companies.

Board served on by other than the CEO Outside directors should be limited to service on the boards of four or fewer public companies.

Former CEOs Former CEOs should not serve on the board of directors.

Chairman/CEO separation The position of chairman and CEO should be separated and the chairman should be an independent outsider.

Board guidelines Board guidelines should be published on the company web site on an annual basis.

Shareholder proposals Management should take action on all shareholder proposals supported by a majority vote within 12 months of the shareholders’ meeting.

Board attendance Directors should attend at least 75% of board meetings.Board vacancies Shareholders should be given an opportunity to vote on

all directors selected to fill vacancies.Related party transaction CEOs should not be the subject of transactions that

create conflicts of interest as disclosed in the proxy statement.

Charter/bylawsPoison pill adoption The company should not have a poison pill in place.

30

Amendment to the charter/bylaws A simple majority vote should be required to amend the charter/bylaws and to approve mergers or business combinations.

Approval of mergers A simple majority vote should be required to approve mergers or business combinations.

Written consent Shareholders should be permitted to act by written consent.

Special meetings Shareholders should be permitted to call special meetings.

Capital structure Declawed preferred stock is viewed favorably.Board amendments Board should not be permitted to amend the bylaws

without shareholder approval.Capital structure-dual class Common stock entitled to one vote is viewed favorably.Executive and director compensationCost of option plans An option-pricing model is used to measure the cost of

all new stock-based incentive plans.Approval of option repricing Plan documents should be written to expressively

prohibit repricing without prior shareholder approval.Approval of option plans All stock-based incentive plans should be submitted to

shareholders for approval.Director compensation Directors should receive a portion of their

compensation in the form of stock.Compensation committee interlocks No interlocking directors should serve on the

compensation committee.Option repricing Options should not have been repriced without

shareholder approvals during the past three years.Option burn rate Burn rates are considered excessive where average

annual option grants exceed 2% of outstanding shares over the past three years or exceed one standard deviation from the industry mean.

Option expensing Companies are moving toward option expensing.Pension plans Non-employee directors do not participate in

company’s pension plans.Corporate loans Company does not provide any loans to executives for

exercising optionsExecutive and director ownershipDirector stock ownership All directors with more than one year of service should

own stock.Stock ownership guidelines-executives Executives should be subject to stock ownership

guidelines.Stock ownership guidelines-directors Directors should be subject to stock ownership

guidelines.Progressive practicesBoard performance reviews A policy of conducting annual board performance

reviews should be disclosed.Meeting of outside directors A policy specifying that directors should meet without

the CEO should be disclosed.CEO succession plan A board-approved CEO succession plan should be in

place and evaluated by the directors periodically.Outside advisors A policy authorizing the board to hire its own advisors

should be disclosed.Director resignation A policy requiring directors to resign upon a change in

job status should be disclosed.

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Retirement age A retirement age or term limits serve as useful tools for ensuring that new board is regularly sought.

State of incorporationIncorporation in a state with anti-takeover provisions

Incorporation in a state without any antitakeover provisions, or opting out of such protections is viewed favorably.

32

Appendix IIVariable definitions

Variable name Variable definitionCGINDEXit Firm i’s governance index in year t, which is defined as the number of

governance provisions that satisfies the minimum standard provided in ISS Corporate Governance: Best Practices User Guide and Glossary (2008).

INVDURit-1 The institutional investment duration of stock i in year t-1, which is defined as INVDURit-1 = Σ[wkit-1 x log(INVDURkit-1)], where wkit-1 is the fraction of firm i’s total institutional ownership held by institution k at the end of year t-1 and Σ denotes the summation over k. To determine the investment duration of institution k in stock i, we first identify the first quarter in which institution k reported its shareholding in firm i. We then measure institution k’s investment duration for firm i at the end of year t-1, INVDURkit-1, by the number of quarters between the first quarter and the last quarter of year t-1.

CONCENTRATIONit-1 Herfindahl index of firm i in year t-1, which is defined as Hit-1 = 100 ∑Skt-

12, where Skt-1 is the fraction of firm i’s shares held by institution k in year

t-1 and ∑ denotes summation over k.IOit-1 The total institutional ownership of firm i in year t-1.FSIZEit-1 The logarithm of firm i’s total assets in year t-1.R&Dit-1 The ratio of firm i’s research and development expenditure to total assets

in year t-1.VOLATILITYit-1 The standard deviation of firm i’s operating profit in the past five years

preceding year t-1.MTBit-1 The ratio of the summation of firm i’s market value of equity and long-

term debt to total assets in year t-1.LEVERAGEit-1 The ratio of firm i’s long-term debt to total assets in year t-1.FCFit-1 The ratio of the difference between firm i’s operating cash flow and

capital expenditure to total assets in year t-1.RETit-1 The buy-and-hold stock returns over the past five years.FIRMAGEit-1 One minus the number of years since firm i first appears in the CRSP.IO_LONGit-1 The total long-term institutional ownership of firm i in year t-1. We

classify an institution as a long-term institution if its length of investment in a firm is longer than two years.

IO_SHORTit-1 The total short-term institutional ownership of firm i in year t-1. We classify an institution as a short-term institution if its length of investment in a firm is shorter than two years.

NOINST_LONGit-1 The number of long-term institutional investors for firm i in year t-1. We classify an institution as a long-term institution if its length of investment in a firm is longer than two years.

NOINST_SHORTit-1 The number of short-term institutional investors for firm i in year t-1. We classify an institution as a short-term institution if its length of investment in a firm is shorter than two years.

SPREADit-1 The bid-ask spread of firm i in year t-1. We calculate the bid-ask spread of stock i on day τ using the following formula: SPREADiτ = (Askiτ – Bidiτ)/Miτ; where Askiτ is the ask price of stock i on day τ, Bidiτ is the bid price of stock i on day τ, and Miτ is the mean of Askiτ and Bidiτ. For each stock, we then calculate the average spread during each year.

IOPit-1 The institutional ownership propensity of firm i in year t-1. We first calculate the mean and standard deviation of institution k’s ownership in

33

firm i over the past 20 quarters. We use the ratio of the mean of the ownership to the standard deviation over the past 20 quarters as institution k’s ownership persistency in firm i at time t-1 (IOPkit-1). We then measure firm i’s institutional ownership persistency at time t-1 by

IOP¿−1=∑N=1

N ¿−1 IOPkit−1

N¿−1, where Nit-1 is the number of institutions which

own firm i’s shares at time t-1.NON-ZERO-POINTS it-1 The number of quarters during which institution k holds non-zero shares.MAINTAIN-STAKE it-1 The number of quarters during which institution k increases or maintains

the ownership stake over the past 20 quarters

34

Appendix IIIThe list of public and private pension funds with 13F filings

Public pension funds Private pension fundsCalifornia Legislators Retirement System Allstate Agents Pension FundsCalifornia Public Employees’ Retirement System Allstate Retirement PlanNew York State Common Retirement Fund Amica Pension fundsState Board of Administration of Florida Atlantic Richfield Co.Teacher Retirement System of Texas Bethlehem Steel PensionNew York State Teachers’ Retirement System Commonwealth Edison Pooled FundState of Wisconsin Investment Board Digital Equipment Pension TrustOhio Public Employees Retirement System DuPont Pension De Nemours & Co.State Teachers’ Retirement System of Ohio Financial Institutions Retirement FundVirginia Retirement System General Electric Insurance Plan TrustPennsylvania Public School Employees’ Retirement General Electric Pension TrustPublic Employees’ Retirement Association of Colorado

General Electric Medcare Trust

Maryland State Retirement & Pension System Grumman Corporation Pension FundAlaska Retirement Management Board IBM Retirement PlanKentucky Teachers’ Retirement System Pichin Corp (TWA Retirement Plans)School Employees of Retirement System of Ohio Trans World Airlines RetirementNew Mexico Educational Retirement Board US Steel and Carnegie PensionMissouri State Employees’ Retirement System YMCA Retirement FundMontana Board of Investments General Motors Investment Management

Lockheed Martin Investment ManagementVerizon Investment ManagementExxon Mobil Investment ManagementCollege Retirement Equities Fund

35

Table 1Distribution of investment duration across stocks by the type of institutions

To determine the investment duration (INVDUR) of institution k in stock i, we first identify the first quarter in which institution k reported its shareholding in firm i from the 13F data provided by Thomson Reuters. We then measure institution k’s investment duration for firm i at the end of year t, INVDURkit, by the number of quarters between the first quarter and the last quarter of year t. To shed some light on the extent to which an institution’s investment duration differs across stocks in its portfolio, we classify stocks in each institution’s portfolio into six different investment duration categories (0-1 year, 1-2 years, 2-3 years, 3-4 years, 4-5 years, and above 5 years) and then calculate the proportion of stocks that belong to each category.

Investment duration (in years)0-1 1-2 2-3 3-4 4-5 > 5

Bank trusts 0.32 0.18 0.12 0.09 0.06 0.23Insurance 0.30 0.17 0.12 0.09 0.07 0.25Investment companies 0.38 0.17 0.11 0.08 0.06 0.20Investment advisors 0.43 0.19 0.11 0.08 0.05 0.14Public pension funds 0.24 0.15 0.11 0.09 0.08 0.33Private pension funds 0.29 0.15 0.10 0.08 0.06 0.32Hedge funds 0.62 0.18 0.08 0.04 0.03 0.05All institutions 0.48 0.19 0.10 0.07 0.04 0.12

36

Table 2Descriptive statistics and correlation matrix

Panel A shows descriptive statistics and Panel B shows the correlation matrix of the variables. CGINDEX is the firm’s governance index, INVDUR is the duration of institutional investment, CONCENTRATION is the Herfindahl index of institutional ownership, IO is the total institutional ownership in each firm, FSIZE is the logarithm of the firm’s total assets, R&D is the ratio of research and development expenditure to total assets, VOLATILITY is the standard deviation of operating profit in the past five years, MTB is the ratio of the summation of market value of equity and long-term debt to total assets, LEVERAGE is the ratio of long-term debt to total assets, FCF is the ratio of the difference between operating cash flow and capital expenditure to total assets, FIRMAGE is the number of years since the firm first appears in the CRSP, and RET is the buy-and-hold stock returns over the past five years. The total number of observations is 19,204. ***, **, and * indicate statistical significance at the 1%, 5% and 10% level, respectively.

Panel A: Descriptive statistics

PercentileMean Std. Dev. Min Max 25 50 75

CGINDEX 24.40 5.19 1.00 42.00 21.00 25.00 28.00INVDUR 2.50 0.64 0.00 3.76 2.13 2.57 2.93CONCENTRARION 2.09 1.84 0.00 10.97 0.70 1.75 2.97IO 0.47 0.28 0.00 0.96 0.23 0.49 0.70FSIZE 5.86 1.97 1.71 10.48 4.43 5.82 7.20R&D 0.06 0.11 0.00 0.74 0.00 0.01 0.07VOLATILITY 0.08 0.12 0.01 0.96 0.02 0.04 0.09MTB 1.92 1.83 0.37 14.21 0.92 1.34 2.18LEVERAGE 0.22 0.22 0.00 1.06 0.01 0.18 0.34FCF 0.01 0.21 -1.24 0.35 -0.01 0.06 0.12FIRMAGE 19.51 15.57 5.00 78.00 9.00 14.00 26.00RET 1.08 2.49 -0.96 14.30 -0.35 0.33 1.45

37

Panel B: Correlation matrix

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

CGINDEX (1) 1.00

INVDUR (2) 0.21*** 1.00

CONCENTRARIO

N (3)

0.14*** 0.15*** 1.00

IO (4) 0.27*** 0.15*** 0.68*** 1.00

FSIZE (5) 0.27*** 0.44*** 0.23*** 0.57*** 1.00

R&D (6) -0.03*** -0.15*** -0.09*** -0.17*** -0.34*** 1.00

VOLATILITY (7) -0.08*** -0.30*** -0.15*** -0.27*** -0.42*** 0.54*** 1.00

MTB (8) -0.08*** -0.20*** -0.11*** -0.02*** -0.19*** 0.43*** 0.41*** 1.00

LEVERAGE (9) -0.02*** 0.06*** 0.03*** -0.01 0.24*** -0.16*** -0.09*** -0.14*** 1.00

FCF (10) 0.08*** 0.17*** 0.12*** 0.29*** 0.39*** -0.68*** -0.57*** -0.28*** 0.02** 1.00

FIRMAGE (11) 0.20*** 0.42*** -0.05*** 0.02*** 0.39*** -0.18*** -0.21*** -0.13*** 0.08*** 0.19*** 1.00

RET (12) -0.06*** -0.17*** -0.01 0.17*** 0.08*** -0.11*** -0.09*** 0.29*** -0.08*** 0.20*** -0.01*

38

Table 3 Corporate governance index as a function of institutional investment duration and other firm attributes

CGINDEXit is firm i’s governance index in year t, INVDURit-1 is the institutional investment duration of stock i in year t-1, CONCENTRATIONit-1 is the Herfindahl index of firm i in year t-1, IO it-1 is aggregate institutional ownership of firm i in year t-1, FSIZEit-1 is the logarithm of firm i’s total assets in year t-1, R&Dit-1 is the ratio of firm i’s research and development expenditure to total assets in year t-1, VOLATILITYit-1 is the standard deviation of firm i’s operating profit in the past five years preceding year t-1, MTBit-1 is the ratio of the summation of firm i’s market value of equity and long-term debt to total assets in year t-1, LEVERAGEit-1 is the ratio of firm i’s long-term debt to total assets in year t-1, FCF it-1 is the ratio of the difference between firm i’s operating cash flow and capital expenditure to total assets in year t-1, RETit-1 is the buy-and-hold stock returns over the past five years, and FIRMAGE it-1 is one minus the number of years since firm i first appears in the CRSP. We estimate the coefficients using the pooled OLS regression with standard errors clustered by firm and year. The figures in parentheses are t-statistics. ***, **, and * indicate statistical significance at the 1%, 5% and 10% level, respectively.

Dependent variable: CGINDEXit

(1) (2)Intercept 17.723***

(31.02)18.054***

(32.92)INVDURit-1 0.496***

(7.95)0.659***(10.60)

CONCENTRATIONit-1 0.243***(11.60)

IOit-1 4.286***(25.79)

FSIZEit-1 0.664***(28.44)

0.298***(10.09)

R&Dit-1 1.830***(4.17)

1.094**(2.53)

VOLATILITYit-1 2.023***(5.44)

2.501***(6.74)

MTBit-1 -0.146***(-5.99)

-0.184***(-7.75)

LEVERAGEit-1 -2.052***(-11.81)

-1.523***(-8.83)

FCFit-1 -0.041(-0.18)

-0.443*(-1.91)

FIRMAGEit-1 0.034***(12.06)

0.045***(15.80)

RETit-1 -0.106***(-6.45)

-0.139***(-8.55)

Industry dummies Yes YesAdjusted R2 0.126 0.148Number of observations 19,204 19,204

39

Table 4Regression using changes in the variables

In Panel A, we regress changes in CGINDEX between year t and t-2 on changes in INVDUR and control variables between year t-1 and t-3. In Panel B, we classify an institution as a long-term (short-term) institution if its length of investment in a firm is longer (shorter) than two years and calculate the total ownership of long-term institutions (IO_LONG) and the total ownership of short-term institutions (IO_SHORT) for each firm. Similarly, we count the number of long-term institutions (NOINST_LONG) and the number of short-term institutions (NOINST_SHORT) for each firm. We regress changes in CGINDEX between year t and t-2 on changes in these and other control variables between year t-1 and t-3. We estimate the coefficients using the pooled OLS regression with standard errors clustered by firm and year. The figures in parentheses are t-statistics. See Appendix II for the definition of each variable. ***, **, and * indicate statistical significance at the 1%, 5% and 10% level, respectively.

Panel A: Regression on changes in investment duration

Dependent variable: ∆CGINDEXit

(1) (2)Intercept 0.927

(1.57)0.828(1.41)

∆INVDURit-1 0.469***(6.75)

0.555***(7.99)

∆CONCENTRATIONit-1 0.047(1.38)

∆IOit-1 2.820***(8.21)

∆FSIZEit-1 -0.037(-0.34)

-0.324***(-2.83)

∆R&Dit-1 1.615**(2.13)

1.516**(2.00)

∆VOLATILITYit-1 4.016***(8.23)

4.098***(8.41)

∆MTBit-1 -0.432***(-16.84)

-0.467***(-17.89)

∆LEVERAGEit-1 -0.901***(-3.23)

-0.662**(-2.37)

∆FCFit-1 -0.100(-0.34)

-0.097(-0.34)


40

Panel B: Regression on changes in the ownership or changes in the number of long-term institutions

Dependent variable: ∆CGINDEXit

(1) (2)Intercept 0.818

(1.28)0.891(1.39)

∆IO_LONGit-1 4.507***(10.50)

∆IO_SHORT it-1 0.467(1.07)

∆NOINST_LONGit-1 0.583***(6.33)

∆NOINST_SHORTit-1 -0.034(-0.53)

∆CONCENTRATIONit-1 0.040(1.12)

∆NOINSTit-1 0.316**(2.50)

∆FSIZEit-1 -0.457***(-3.37)

-0.247*(-1.84)

∆R&Dit-1 1.527*(1.89)

1.764**(2.19)

∆VOLATILITYit-1 4.480***(7.89)

4.464***(7.84)

∆MTBit-1 -0.540***(-18.55)

-0.499***(-17.22)

∆LEVERAGEit-1 -0.827***(-2.69)

-1.018***(-3.30)

∆FCFit-1 -0.240(-0.77)

-0.224(-0.71)


41

Table 5Regressions of governance category on institutional investment duration

To determine which governance categories are related to institutional investment duration, we regress CGINDEX for each one of the six governance categories in the ISS database on the same set of explanatory and control variables that are included in regression model (1). We estimate the coefficients using the pooled OLS regression with standard errors clustered by firm and year. The figures in parentheses are t-statistics. See Appendix II for the definition of each variable. ***, **, and * indicate statistical significance at the 1%, 5% and 10% level, respectively.


Governance categoriesAUDIT BOARD CHARTER/

BYLAWSCOMPENSATION OWNERSHIP PROGRESSIVE

PRACTICES(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Intercept 2.364***(26.74)

2.374***(26.81)

6.067***(22.75)

6.249***(24.42)

4.256***(25.28)

4.213***(25.66)

4.711***(29.80)

4.706***(29.69)

0.634***(7.60)

0.688***(8.77)

-0.356*(-1.77)

-0.223(-1.20)

INVDURit-1 0.095***(8.51)

0.099***(8.86)

0.171***(5.70)

0.261***(8.71)

-0.031(-1.58)

-0.048**(-2.45)

0.073***(4.52)

0.072***(4.47)

0.017(1.56)

0.043***(4.04)

0.168***(7.93)

0.231***(10.93)

CONCENTRATIONit-1 0.002(0.69)

0.133***(13.79)

-0.017***(-2.77)

0.001(0.20)

0.037***(9.97)

0.088***(11.77)

IO it-1 0.135***(4.71)

2.348***(31.08)

-0.566***(-11.53)

-0.065(-1.53)

0.708***(23.03)

1.736***(30.16)

FSIZEit-1 -0.050***(-12.35)

-0.062***(-12.49)

0.316***(29.09)

0.115***(8.66)

-0.099***(-13.66)

-0.047***(-5.51)

0.006(0.95)

0.012*(1.68)

0.133***(30.94)

0.071***(13.45)

0.364***(45.93)

0.214***(21.61)

R&Dit-1 -0.064(-0.82)

-0.089(-1.14)

1.525***(6.92)

1.121***(5.20)

-0.593***(-4.17)

-0.049***(-3.44)

-0.351***(-2.89)

-0.338***(-2.78)

0.467***(6.09)

0.344***(4.52)

0.730***(4.80)

0.427***(2.86)


0.222***(3.37)

0.739***(4.06)

1.001***(5.57)

0.296**(2.57)

0.223*(1.95)

0.184*(1.81)

0.174*(1.71)

0.214***(3.76)

0.295***(5.23)

0.379***(2.92)

0.579***(4.48)

MTBit-1 -0.048***(-12.02)

-0.049***(-12.28)

-0.057***(-5.00)

-0.078***(-7.03)

-0.008(-1.21)

-0.004(-0.59)

-0.011*(-1.90)

-0.010*(-1.84)

0.012***(3.17)

0.006*(1.62)

-0.034***(-4.19)

-0.049***(-6.27)

LEVERAGEit-1 -0.145***(-4.88)

-0.128***(-4.27)

-0.980***(-11.86)

-0.690***(-8.47)

-0.081(-1.60)

-0.153***(-2.99)

0.180***(4.20)

0.171***(3.97)

-0.217***(-7.24)

-0.129***(-4.32)

-0.776***(-12.84)

-0.560***(-9.41)

FCFit-1 -0.025(-0.60)

-0.038(-0.93)

-0.132(-1.15)

-0.352***(-3.14)

-0.018(-0.25)

0.038(0.52)

0.110*(1.77)

0.117*(1.88)

0.072*(1.77)

0.005(0.12)

-0.086(-1.05)

-0.250***(-3.12)

FIRMAGEit-1 0.001*(1.92)

0.001***(2.86)

0.017***(14.06)

0.023***(18.91)

0.001(1.02)

-0.001(-1.19)

0.002**(2.52)

0.001**(2.10)

0.005***(9.75)

0.001***(13.34)

0.009***(9.28)

0.014***(14.07)

RETit-1 -0.011***(-4.02)

-0.012***(-4.38)

-0.037***(-4.84)

-0.054***(-7.34)

0.024***(5.32)

0.028***(6.22)

-0.048***(-13.40)

-0.048***(-13.24)

-0.001(-0.40)

-0.006**(-2.30)

-0.033***(-5.99)

-0.046***(-8.41)

Industry dummies Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes YesAdjusted R2 0.028 0.029 0.130 0.161 0.040 0.046 0.028 0.028 0.144 0.144 0.195 0.225Number of observations 19,204 19,204 19,204 19,204 19,204 19,204 19,204 19,204 19,204 19,204 19,204 19,204

42

Table 6Relation between corporate governance and institutional investment duration by institutional type

To examine whether the effect of institutional investment duration on corporate governance varies with the type of institutions, we conduct regression analysis for each type of institutions. The first three columns show the results when we include the investment duration (INVDUR_TYPE) of public pension funds, private pension funds, or hedge funds as an explanatory variable in the regression model. [Appendix III shows the list of public and private pension funds.] The next four columns show the results when we include the investment duration of bank trusts, insurance companies, investment companies, or investment advisors as an explanatory variable. In each of these regressions, we also include the investment duration of all other types of institutional investors (INVDUR_OTHER TYPE). Hence, for example, we include both the investment duration of public pension funds and the investment duration of all other institutional investors in the regression model for public pension funds. Similarly, we include both the ownership of each type of institutional investors (IO_TYPE) and the total ownership of all other institutional investors (IO_OTHER TYPE) in the regression model for each type of institutional investors to assess the effect of ownership level on corporate governance. We estimate the model using the ordinary least squares (OLS) method with standard errors clustered by firm and year. The figures in parentheses are t-statistics. See Appendix II for the definition of each variable. ***, **, and * indicate statistical significance at the 1%, 5% and 10% level, respectively.


Type of institutionPublic

pension fundPrivate

pension fundHedge fund Bank Insurance Investment

companyInvestment advisory

(1) (2) (3) (4) (5) (6) (7)Intercept 17.719***

(28.71)14.189***(16.71)

17.044***(27.15)

18.116***(32.55)

15.987***(23.94)

17.718***(31.25)

18.320***(32.75)

INVDUR_TYPEit-1 2.015***(3.69)

0.968(0.37)

0.726***(5.71)

1.71***(9.27)

1.783***(4.67)

0.857***(9.90)

1.190***(12.40)

IO_TYPEit-1 -12.198***(-2.89)

-52.395**(-2.50)

11.133***(16.73)

3.399***(4.19)

-12.445***(-4.81)

0.864(1.05)

-0.094(-0.21)

INVDUR_OTHER TYPEit-1

0.932***(12.24)

1.786***(14.54)

1.010***(12.47)

0.631***(9.40)

1.192***(13.75)

0.899***(11.29)

0.417***(5.86)

IO_OTHER TYPEit-1 4.758***(21.55)

6.234***(20.48)

2.486***(9.52)

4.688***(17.34)

5.622***(25.85)

4.967***(21.54)

7.824***(21.88)

FSIZEit-1 0.278***(8.58)

0.452***(10.14)

0.357***(11.00)

0.269***(8.75)

0.394***(11.57)

0.312***(9.84)

0.262***(8.55)

R&Dit-1 1.037**(2.05)

1.248*(1.71)

0.604(1.27)

1.159***(2.59)

0.956*(1.68)

1.026**(2.24)

0.975**(2.19)


3.838***(5.71)

2.740***(6.70)

2.584***(6.58)

3.318***(6.58)

2.580***(6.27)

2.574***(6.64)

MTBit-1 -0.202*** -0.232*** -0.171*** -0.197*** -0.203*** -0.185*** -0.181***

43

(-7.66) (-7.10) (-6.84) (-8.11) (-7.38) (-7.42) (-7.58)LEVERAGEit-1 -1.602***

(-8.04)-1.996***(-7.93)

-1.724***(-9.11)

-1.504***(-8.40)

-1.623***(-7.68)

-1.615***(-8.80)

-1.499***(-8.42)

FCFit-1 -0.573**(-2.09)

-0.940**(-2.45)

-0.698***(-2.74)

-0.493**(-2.04)

-0.743**(-2.46)

-0.614**(-2.47)

-0.493**(-2.06)

FIRMAGEit-1 0.042***(13.83)

0.034***(9.86)

0.044***(14.67)

0.045***(15.50)

0.040***(12.79)

0.042***(14.19)

0.045***(15.64)

RETit-1 -0.128***(-7.57)

-0.119***(-5.82)

-0.128***(-7.69)

-0.135***(-8.20)

-0.128***(-7.16)

-0.140***(-8.38)

-0.130***(-7.96)

Industry dummies Yes Yes Yes Yes Yes Yes YesAdjusted R2 0.136 0.167 0.150 0.147 0.159 0.150 0.151Number of observations 16,545 12,935 17,595 18,687 15,730 18,271 18,626

44

Table 7Liquidity, institutional investment duration, and corporate governance

We calculate the bid-ask spread of stock i on day τ using the following formula: SPREAD iτ = (Askiτ – Bidiτ)/Miτ; where Askiτ is the ask price of stock i on day τ, Bid iτ is the bid price of stock i on day τ, and M iτ is the mean of Askiτ and Bidiτ. For each stock, we then calculate the average spread during each year from 2000 through 2008. We include both the spread and the interaction variable between the spread and institutional investment duration in the regression model. We estimate the model using the ordinary least squares (OLS) method with standard errors clustered by firm and year. The figures in parentheses are t-statistics. See Appendix II for the definition of each variable. ***, **, and * indicate statistical significance at the 1%, 5% and 10% level, respectively.


(1) (2)Intercept 20.896***

(30.82)20.557***(30.90)

INVDURit-1 1.679***(16.74)

1.797***(17.96)

SPREADit-1 -1.078***(-6.98)

-0.855***(-5.55)

INVDUR×SPREADit-1 -0.482***(-7.98)

-0.523***(-8.73)


IOit-1 1.812***(10.12)

FSIZEit-1 -0.008(-0.27)

-0.123***(-3.73)

R&Dit-1 -0.427(-0.75)

-0.689(-1.21)


2.638***(5.47)

MTBit-1 -0.344***(-13.35)

-0.348***(-13.60)

LEVERAGEit-1 -0.094(-0.48)

0.001(0.00)

FCFit-1 0.308(1.05)

0.085(0.29)

FIRMAGEit-1 0.036***(13.02)

0.040***(14.35)

RETit-1 -0.151***(-9.45)

-0.155***(-9.75)


45

Table 8Alternative measures of institutional investment duration

In this table we use the following three alternative measures of institutional investment duration to assess the robustness of our results: the persistency of institutional ownership, the non-zero-points duration, and the maintain-stake-points duration. We first calculate the mean and standard deviation of institution k’s ownership in firm i over the past 20 quarters. We use the ratio of the mean of the ownership to the standard deviation over the past 20 quarters as institution k’s ownership persistency in firm i at time t-1 (IOPkit-1). We

then measure firm i’s institutional ownership persistency at time t-1 by IOP¿−1=∑N=1

N ¿−1 IOPkit−1

N¿−1

, where Nit-1

is the number of institutions which own firm i’s shares at time t-1. The non-zero-points duration is the number of quarters during which institution k holds non-zero shares. The maintain-stake-points duration is the number of quarters during which institution k increases or maintains the ownership stake over the past 20 quarters. For the firm-level duration, both duration measures are averaged across all institutions in the firm’s ownership structure. We estimate the model using the ordinary least squares (OLS) method with standard errors clustered by firm and year. The figures in parentheses are t-statistics. See Appendix II for the definition of each variable. ***, **, and * indicate statistical significance at the 1%, 5% and 10% level, respectively.


Measures of investment durationIOP NON-ZERO-POINTS MAINTAIN-STAKE

(1) (2) (3) (4) (5) (6)Intercept 17.763***

(31.33)18.183***

(33.43)17.889***

(31.01)17.889***

(31.13)18.491***

(32.51)19.010***

(34.65)INVDURit-1 1.032***

(10.52)1.310***

(13.31)0.176***

(11.94)0.190***

(13.11)0.028(1.33)

0.053**(2.50)


0.237***(11.35)

0.255***(12.13)

IOit-1 4.415***(26.64)

4.192***(25.31)

4.200***(25.25)

FSIZEit-1 0.739***(32.54)

0.387***(13.56)

0.653***(28.17)

0.306***(10.50)

0.708***(30.93)

0.366***(12.60)

R&Dit-1 1.996***(4.54)

1.300***(2.99)

1.649***(3.78)

0.945**(2.20)

1.951***(4.44)

1.279***(2.95)


2.657***(7.12)

2.219***(6.01)

2.598***(7.05)

1.656***(4.47)

2.023***(5.48)

MTBit-1 -0.146***(-6.00)

-0.186***(-7.86)

-0.129***(-5.31)

-0.166***(-7.00)

-0.148***(-6.04)

-0.186***(-7.78)

LEVERAGEit-1 -2.044***(-11.75)

-1.504***(-8.71)

-2.082***(-12.00)

-1.586***(-9.21)

-2.127***(-12.21)

-1.634***(-9.45)

FCFit-1 -0.189(0.42)

-0.644***(-2.76)

0.034(0.14)

-0.365(-1.58)

-0.101(-0.43)

-0.515**(-2.22)

FIRMAGEit-1 0.032***(11.14)

0.043***(14.86)

0.031***(11.01)

0.043***(14.98)

0.039***(13.92)

0.051***(17.73)

RETit-1 -0.113***(-6.97)

-0.150***(-9.39)

-0.074***(-4.43)

-0.108***(-6.60)

-0.124***(-7.38)

-0.158***(-9.57)

Industry dummies Yes Yes Yes Yes Yes YesAdjusted R2 0.128 0.151 0.129 0.150 0.123 0.144Number of observations 19,204 19,204 19,204 19,204 19,204 19,204

46

Documents

Investment Duration and Corporate Governance