The Effect of Hedge Fund Activism on Corporate Tax Avoidance*

C.S. Agnes Cheng

E. J. Ourso College of Business

Louisiana State University

Baton Rouge, LA 70803

Tel: (225) 578-6215, E-mail: acheng@lsu.edu

Henry He Huang

College of Business Administration

Prairie View A&M University

Prairie View, TX 77446

Tel: (936) 261-9210, E-mail: hhuang@pvamu.edu

Yinghua Li

Krannert School of Management

Purdue University

West Lafayette, IN 47907-2056

Tel: (765) 496-3510, E-mail: yli@purdue.edu

Jason Stanfield

Krannert School of Management

Purdue University

West Lafayette, IN 47907-2056

Tel: (765) 494-6501, E-mail: jwstanfield@purdue.edu

June 2010

* We thank Ryan Wilson, Pete Lisowsky, and Thomas Omer for their helpful comments. We are grateful to Wei

Jiang and Fei Pan for sharing the hedge fund data. We also thank Shanshan Pan and Hongbo Zhang for their

excellent research assistance.

The Effect of Hedge Fund Activism on Corporate Tax Avoidance

ABSTRACT

Prior literature suggests that the net benefits of tax avoidance are contingent on a firm‟s

ability to constrain its managerial opportunism. We thus test the implications of tax avoidance

for firm value in the presence of improved shareholder monitoring. Specifically, we examine the

impact of a group of increasingly important external monitors, activist hedge funds, on corporate

tax avoidance and firm value. Using a change analysis, we find that target firms of hedge fund

activism increase their levels of tax avoidance for a persistent period of time. More importantly,

we find that the increase in tax avoidance is associated with an increase in the target firm's value.

Finally, preliminary evidence indicates that these greater tax savings result from more efficient

tax management as opposed to increased use of high-risk and potentially illegal tax strategies

such as sheltering, or temporary deferral of taxes to future periods. Overall, our evidence

suggests that hedge fund activists, by providing informed monitoring, are able to induce value-

enhancing changes in tax policies.

JEL Classification: G32; G34; H26.

Keywords: Tax Avoidance; Hedge Fund Activism; Corporate Governance.

1

The Effect of Hedge Fund Activism on Corporate Tax Avoidance

Tax avoidance can have a significant positive impact on firm value if it leads to a transfer

of wealth from the government to shareholders. Such avoidance, however, is not costless, and the

classical cost-benefit analysis involves the trade-off between tax savings and potential penalties

and reputation damages if the avoidance is later ruled as improper (e.g., Chen et al. 2010). More

recently, an additional cost has been considered in the tax avoidance literature – increased

latitude for managerial opportunism afforded by tax avoidance activity (the so-called “agency

costs” of tax avoidance). Due to these agency costs and the opaque nature of tax avoidance

activities, the impact of tax avoidance on firm value is thus contingent on the strength of firm

governance (Chen and Chu 2005, Crocker and Slemrod 2005, Desai and Dharmapala 2006,

2009). When governance is weak, tax avoidance activities can be used to mask rent extraction

and reduce firm value. For instance, a number of firms involved in recent corporate scandals,

including Dynergy, Enron, Tyco, and WorldCom, engaged in complex tax transactions to

mislead investors about their financial performance (e.g., Desai 2005, Desai and Dharmapala

2006, Graham and Tucker 2006, Slemrod 2004). Further, Desai and Dharmapala (2009) show

that tax avoidance improves firm value only in the presence of strong governance, measured by

high levels of institutional ownership. We build on these findings and test the joint effect of

governance strength and tax avoidance on firm value by adopting a change analysis. We

conjecture that increases in tax avoidance accompanied by increased monitoring from hedge

fund activism will lead to higher firm value.

We choose to study the impact of hedge fund activism on tax avoidance for several

reasons. First, prior literature finds that hedge fund activism strengthens shareholder monitoring

2

and mitigates agency costs and thus could be a good indicator of improved corporate

governance. Briggs (2007), Brav et al. (2008), and Klein and Zur (2009) document increases in

dividend payout, CEO turnover, and board representation after hedge fund activism. Second,

hedge funds play an increasingly important role in the capital markets and their activities have

significant economic implications (Khan and Rock 2007). Hedge fund activism is an effective

form of shareholder activism and its implications for corporate decisions and firm value are of

interest in their own right. Although announcements of hedge fund activism often generate

positive abnormal returns to target firms, it is unclear whether the increase in firm value is

caused by the stock picking effect, the takeover effect, or hedge fund monitoring (Brav et al.

2008, Greenwood and Schor 2009).1 In this study, we directly link changes in tax avoidance

following hedge fund interventions to changes in firm value, bridging a gap in the literature by

providing evidence on the association between monitoring activities and firm value. Finally, in

their review of the empirical tax literature, Shackelford and Shevlin (2001) point out

that ownership structure is an important but under-studied determinant of corporate tax policies.

We add to the literature by examining the impact of sophisticated shareholders (specifically,

hedge fund activists) on tax avoidance.

Why are hedge funds able to influence corporate tax policies? Dyreng et al. (2008) show

significant variation in the level of corporate tax avoidance. While some of the variation is

attributable to factors such as size and industry, a significant portion remains unexplained. One

potential source of this variation is differences in managerial ability and motivation for firm-

level tax planning. That is, managers‟ lack of tax planning expertise and their preference to avoid

additional effort and risk associated with tax planning might have contributed to some firms‟ low

1

The stock picking effect refers to the possibility that the announcement of hedge fund targeting signals

undervaluation of the firm (Brav et al. 2008). The takeover effect refers to the argument by Greenwood and Schor

(2009) who attribute the positive announcement returns to activists‟ ability to force the target firms into a takeover.

3

levels of tax avoidance. Hedge fund activists likely possess or have access to sophisticated tax

expertise, and can provide informed monitoring by pushing managers to improve tax planning

efficiency. 2

In particular, hedge fund activists have concentrated ownership and their returns can

be significantly affected by the performance of an individual firm (Kahan and Rock 2007, Brav

et al. 2008). Therefore, they have incentives to utilize their influence to push individual firms to

adopt tax avoidance strategies that improve after-tax cash flows and firm value.

Anecdotal evidence demonstrates that activist hedge funds acknowledge the importance

of tax planning to firm performance and value, and they sometimes demand specific changes in

corporate tax strategies to reduce tax inefficiencies. For instance, in 2007, hedge fund Third

Point LLC targeted PDL Biopharma Inc., aiming to change the firm‟s business strategies and to

remove its CEO Mark McDade. In making their case to the board of directors, they wrote: “Mr.

McDade lacks the ability to communicate with the investment community effectively in part

because he has a poor understanding of even basic financial concepts… He readily admitted to

us that he has not properly thought through nor effectively utilized PDL‟s tax credits, which has

and will result in reduced value for PDL shareholders” (Third Point LLC vs. PDL Biopharma

2007).3 Calling the unused credits a “readily exploitable Company asset”, Third Point identifies

the firm‟s tax strategy as a potential source of value improvement.

Following prior literature (e.g. Brav et al. 2008, Greenwood and Schor 2009, Klein and

Zur 2009), we use a hedge fund‟s filing of Schedule 13D as the initiation of hedge fund activism.

We collect such filings from 1994 to 2008 and construct a large sample of 2,981 hedge fund

activist events. We define tax avoidance as activities that reduce explicit taxes per dollar of pre-

tax accounting earnings (Hanlon and Heitzman 2010), and infer a target firm‟s tax avoidance

2 Badertscher et al. (2009) make similar arguments for the tax expertise of private equity managers.

3 For details, please refer to http://www.sec.gov/Archives/edgar/data/882104/0000899140-07-001301.txt.

4

level from four commonly-used metrics.4 The first two metrics are based on effective tax rates

(ETR), measured as a firm‟s income tax expense and cash taxes paid scaled by pretax income,

respectively. The other two, based on the difference between a firm‟s reported income and

taxable income (book-tax difference, or BTD), are the Manzon-Plesko (2002) book-tax

difference and a derivative BTD measure proposed by Desai and Dharmapala (2006). We predict

lower ETRs and larger BTDs following hedge fund activist events attributable to increased

shareholder monitoring. As expected, we find increases in tax avoidance under all four measures.

We also obtain consistent results using a multivariate regression model that controls for other

determinants of tax avoidance identified in the literature.

We then focus on whether these increases in tax avoidance lead to increases in firm

value. Following Desai and Dharmapala (2009) and many other studies in the literature, we use

Tobin‟s Q as the proxy for firm value. We find that these increases in tax avoidance after hedge

fund interventions are associated with significant increases in the target firms‟ Tobin‟s Q.

Furthermore, the increases in tax avoidance in hedge fund target firms do not fully reverse in the

long term (five years after the intervention), which suggests that changes in tax avoidance are

likely associated with long-term changes in firms‟ tax policies.

To ensure it is the hedge fund influence that drives the positive association between tax

avoidance and firm value, we compare a subsample of firm-years that have hedge fund activist

block ownership with a subsample in which hedge fund activists no longer hold a significant

stake. We find that the change in tax avoidance is value-enhancing only when hedge fund

4 To avoid the complexity of determining the legality or appropriateness of the mechanism used to reduce the tax

burden, we follow the literature (e.g., Chen et al. 2010, Frank et al. 2009, Hanlon and Heitzman 2010) and define tax

avoidance as a broad description of tax strategies that reduce taxes relative to book income rather than a narrower

construct such as tax evasion. Throughout this study we provide evidence of changes in tax avoidance, but not the

mechanism through which the avoidance is achieved. We consider tax aggression as tax management that exceeds

the optimal level of avoidance. One might conjecture that tax aggression results in the observed increase in tax

avoidance following hedge fund intervention. But as discussed in Section IV.C, we do not find a contemporaneous

increase in the estimated probability of tax sheltering, which supports our focus of avoidance rather than aggression.

5

activists maintain significant influence over target firms. This result further corroborates our

hypothesis that hedge funds‟ informed monitoring decreases the agency costs of tax avoidance.

We also analyze whether the increase in tax avoidance in target firms is driven by the

firms‟ increased use of tax planning strategies that are high-risk and potentially illegal (e.g., tax

sheltering) or avoidance activities that only create temporary BTD differences. Using Wilson‟s

(2009) sheltering model, we find no evidence that target firms have a higher likelihood of

engaging in tax sheltering after hedge fund intervention. We also find evidence that our results

are not driven by temporary deferral of tax burdens to future periods. Our results suggest the

greater tax savings in target firms are more likely to result from more efficient tax planning

rather than the use of egregious and risky tax evasion strategies or temporary tax deferrals.

This paper makes several contributions. First, our study contributes to the line of research

on the effect of tax avoidance on firm value. We extend Desai and Dharmapala (2009) by

examining a unique setting in which firms experience an increase in shareholder scrutiny (a

positive shock to governance). Our findings support Desai and Dharmapala‟s conclusion that tax

avoidance increases firm value in the presence of effective monitoring, and more generally,

further validate the examination of tax avoidance within an agency framework. Second, our

research establishes a direct linkage between hedge fund monitoring activities and firm value.

We find a positive association between the increase in the tax avoidance level and the increase in

the Tobin‟s Q for target firms, which suggests that hedge fund activists push firms to reduce

inefficiencies in tax management to increase after-tax cash flows and improve firm value. In

particular, such a positive association only exists when hedge fund activists have significant

influence over target firms. Finally, we contribute to the growing literature on the effect of

ownership structure on tax avoidance. Chen et al. (2010) find that family firms engage in less tax

6

avoidance than non-family firms and interpret their findings as indicating tax avoidance activities

in family firms could be perceived as rent-seeking activities by minority shareholders.

Badertscher et al. (2009) find that tax avoidance decreases as private equity (PE) takes a major

stake in a firm, which they attribute to the high leverage in PE-backed firms creating tax benefits

and mitigating the need for further tax avoidance. We add to this literature by showing activist

hedge funds, another class of sophisticated owners, have the motivation and ability to improve

corporate tax planning efficiencies. Taken together, our results suggest that hedge fund activists

appear to be directing target firms toward the optimal tax avoidance level rather than pursuing

risky and potentially illegal tax strategies.

The remainder of the paper is organized as follows. Section I presents the related

literature and develops our hypotheses. Section II details our sample and provides the primary

results of the study. Section III discusses additional results, and Section IV examines the

sensitivity of our results to alternative tests and specifications. Section V discusses and

concludes.

I. Literature Review and Hypothesis Development

A. Implications of Tax Avoidance for Firm Value

A growing body of literature focuses on the determinants and consequences of corporate

tax avoidance.5 Of particular interest to our study is the implication of tax avoidance for firm

value, for which two different perspectives have been considered in the literature. In the

traditional perspective, tax avoidance should be demanded by shareholders, as a decrease in

taxes paid increases the cash flow available for investment and distribution to shareholders, a

desirable outcome for the firm (e.g., Graham and Tucker 2006, Desai and Dharmapala 2009). On

5 Please refer to Hanlon and Heitzman (2010) for a detailed survey of the emerging tax avoidance literature.

7

the other hand, the agency view proposes the benefit of tax avoidance could be diminished by the

separation of ownership and control in public firms. Allingham and Sandmo (1972) and Slemrod

(2004) note that in widely-held corporations this separation introduces the agency problem as an

determinant of tax compliance in addition to classical factors (such as statutory rates, the

probability and expected costs of detection, and risk aversion). Chen and Chu (2005) and

Crocker and Slemrod (2005) develop a theoretical foundation to analytically consider the

interaction of tax avoidance, firm value, and the agency problem, and show that the separation of

control and ownership is an important determinant of corporate tax policy. If there are no agency

costs associated with tax avoidance, firms should provide appropriate incentives through

managerial compensation contracts to encourage tax-efficient agent behavior. With these

incentives, explicit or implicit, managers pursue all projects that maximize profits, including

those that reduce tax liabilities, as long as the marginal benefits from tax avoidance exceed the

marginal costs. Similar to other agency problems, however, situations can arise in which the

managers act in their own interests rather than in those of shareholders with regards to tax

decisions. The misalignment between the incentives of managers and owners creates the

possibility that tax strategies are value-enhancing to the manager, but not necessarily to the firm.

Tax avoidance (or lack thereof) can therefore be examined in the context of the agency

framework (Hanlon and Heitzman 2010). Desai and Dharmapala (2006, 2009) identify this view

as an “agency perspective on tax avoidance” or more generally as the “corporate governance

view of taxation”. Since tax avoidance strategies often involve complicated transactions between

“tax-indifferent” related parties, these opaque mechanisms can be employed by managers to

mask rent seeking activities in addition to shielding income from taxation (Desai and

Dharmapala 2006).

8

Corporate governance mechanisms are widely held to be an effective defense against

agency problems and thus could constrain managers‟ ability to use tax avoidance for rent

extraction (Desai et al. 2007, Desai and Dharmapala 2008, 2009). Examining the relation

between tax avoidance and firm value, Desai and Dharmapala (2009) find that tax avoidance is

positively associated with firm value only when corporate governance is effective (as proxied by

high levels of institutional ownership). Wilson (2009) shows that tax sheltering activities

increase firm value only in well-governed firms (as indicated by strong shareholder rights).

Hanlon and Slemrod (2009) provide empirical support for cross-sectional variation in the stock

price reaction to the report of a firm‟s engagement in tax sheltering. They find that on average

there is a significant negative market reaction to such news, consistent with the agency

perspective and investors‟ concern about suboptimal tax avoidance such as overly aggressive

sheltering.

B. Shareholder Activism, Tax avoidance, and Firm Value

Both theoretical and archival evidence in the preceding section indicates that corporate

governance plays a crucial role in determining the impact of tax avoidance on firm value. In this

study, we argue that hedge fund activism can increase the net benefits of tax avoidance by

improving corporate governance and restricting managerial opportunism.

Hedge funds are often portrayed as opportunistic investors interested in extracting short-

term returns (Boyson and Mooradian 2007, Kahan and Rock 2007).6

However, a number of

recent papers establish hedge fund activism as an effective means of shareholder monitoring

6 Hedge funds generally have four characteristics: (1) they are privately-organized investment vehicles with pooled

capital; (2) they are managed by professional investment managers; (3) they are exempted from registration

requirements and securities regulations since they have 100 or fewer beneficial owners or all of their investors are

“qualified” individuals or institutions with high net-worth; and (4) they do not sell products (e.g., Kahan and Rock

2007, Brav et al. 2008).

9

based on the evidence of the post-intervention improvements in governance structure, capital

structure, and operational decisions. Brav et al. (2008) find that hedge funds are successful in

mitigating agency costs and improving firm value. Target firms in their sample experience

increases in payout, higher rates of CEO turnover, and improvements in operating performance

and corporate governance. They also argue that not all hedge fund activists are short-term

focused because they have an average holding period of about 20 months and the positive impact

brought upon the target firm does not fully dissipate even after the fund‟s exit. Similarly, Klein

and Zur (2009) report that hedge fund activism achieves great success in getting target firms to

repurchase their own stocks and replace the CEOs, and increase board representation of the fund.

They also document that hedge funds are able to address agency costs of free cash flow by

increasing dividend payouts. Boyson and Mooradian (2007) show that from 1994 to 2005 hedge

fund activists improve their target firms‟ short-term and long-term performance especially when

they pursue governance improvements, for which they had an overall success rate of about two

thirds. Bratton (2006) concludes that hedge fund activists, as aggressive monitors, have achieved

remarkable success in obtaining board seats using the proxy system. Briggs (2007) demonstrates

that hedge fund activists have become a real power in improving corporate governance through

proxy fights and there is little evidence of hedge fund short-termism. Clifford (2008) finds that

firms targeted by hedge funds for active monitoring and investment purposes earn larger excess

stock returns and exhibit greater increases in return on assets than firms targeted for passive

purposes. He attributes the finding to divestiture of under-performing assets after hedge fund

intervention. Greenwood and Schor (2009), on the other hand, attribute the documented positive

returns of target firms to hedge funds‟ abilities to force target firms into a takeover. Zur (2009)

10

argues that hedge funds‟ reputation brings credibility to their future interventions and motivates

them to exert monitoring efforts.

Hedge funds have incentives and abilities to influence their target firms‟ tax avoidance

activities for several reasons. First, compared with other institutions, hedge fund activists have

stronger incentives to engage in costly monitoring activities since they are less susceptible to the

free rider issue and fund managers have higher pay incentives. The free rider problem predicts

that a shareholder usually lacks the incentive to monitor the firm because the cost of monitoring

often exceeds the shareholder‟s pro rata benefit from the monitoring (Grossman and Hart 1980,

Gillan and Starks 2000). Hedge funds are largely unregulated and are not subject to the “prudent

man” regulations, and they can accumulate a large stake in an individual company (Clifford

2008). As a result, hedge funds have incentives to undertake monitoring activities to improve

operational performance because their marginal returns (pro rata benefit) from the improved

firm governance and performance likely exceed their monitoring costs. In addition, hedge fund

managers‟ pay depends largely on their funds‟ absolute returns (Kahan and Rock 2007). Hedge

funds are not subject to the diversification rule in the Investment Company Act and thus are

relatively undiversified (Brav et al. 2008, Kahan and Rock 2007). Consequently, a hedge fund

can invest a large proportion of its wealth in individual firms and has incentives to influence

these individual firms‟ operations, such as reducing tax payments to generate absolute returns.

Second, increases in tax avoidance can help hedge funds achieve their goals of improving

firm value. Shareholder activism is characterized as a response to the potential gains from

addressing agency conflicts and reducing inefficiencies in publicly-traded corporations (Gilian

and Stark 2000). Therefore, one important source of gains from intervention comes from the

economic benefits of redirecting firms to optimal behaviors and constraining inefficient

11

managerial actions (Maug 1998). Tax avoidance increases firm value by generating tax savings

that potentially improve both accounting earnings and cash flows (Hanlon and Heitzman 2010),

which should also benefit hedge fund activists and increase the value of their investments. With

combined statutory tax rates in excess of one third of a company‟s profits, tax avoidance

provides a significant opportunity for hedge fund activists to increase free cash flow, firm value,

and the value of their investments.

Finally, hedge funds also have the expertise and ability to push for more efficient tax

management. Hedge funds are sophisticated investors who are capable of improving firm value

(Khan and Rock 2007) and possess or can obtain expert tax planning knowledge. Badertscher et

al. (2009) find that firms backed by private equity ownership utilize more tax avoidance since

private equity managers are sophisticated investors with tax expertise. Similar to private equity

funds, hedge funds likely also possess tax expertise, experience, and financial resources to make

tax planning successful.7 Hedge fund activists can also set „the tone at the top‟, analogous to the

effect of top managers on tax avoidance (Dyreng et al. 2010), by emphasizing the importance of

tax planning to the target firm. In addition, hedge funds have the ability to demand changes in

tax strategies. Hedge funds have relatively high percentages of ownership and can use leverage

and derivative instruments to obtain beneficial ownerships or voting rights (Hu and Black 2007)

and use their shareholder rights to nominate and elect board members (Bratton 2006, Briggs

2007, Klein and Zur 2009). They frequently use public media to push for corporate changes and

cooperate with other institutional investors to make their interventions successful (Brav et al.

2008). They can even acquire the target firm if their demands are not met. Therefore, managers

of target firms are likely to meet hedge funds‟ demands for more tax avoidance.

7 Prior literature suggests a linkage between tax expertise and the level of tax avoidance. Bonner, Davis, and Jackson

(1992) find a positive relation between accountants‟ tax knowledge and tax planning performance. McGuire, Omer,

and Wang (2010) show that industry expertise of the external auditor affects the firm‟s tax avoidance level.

12

Anecdotal evidence gives credence to our hypothesis. When targeting BNS Co. in 2002,

hedge fund Hummingbird Management, LLC stated that,

“Our motivation is purely financial; we only seek to maximize returns from our

investment. The important goals are to maximize returns on remaining assets

while minimizing taxes and ongoing costs, thereby maximizing the ultimate cash

payment, to the owners of the company” (Hummingbird vs. BNS Co. 2002).8

This activist statement is consistent with hedge fund activists‟ intent to use better tax

planning to increase firm value. In this filing, Hummingbird also proposes a specific change in

tax strategy, exhibiting its knowledge and expertise in tax planning.

“We feel that efforts should be made to fully utilize the company’s NOL (net

operating loss). Using the NOL to shield income thrown off from the building and

from the proceeds from asset sales would minimize tax expense to the company.”

Based on the above discussions, we propose the first hypothesis as below:

Hypothesis 1: Firms targeted in hedge fund activism exhibit higher levels of tax

avoidance after the activist event.

Although tax avoidance is not solely a reflection of agency problems (Hanlon and

Heitzman 2010, page 27), its effects can be exacerbated or mitigated depending on the firm‟s

particular corporate governance environment (Wilson 2009, Desai and Dharmapala 2009). Tax

avoidance strategies often involve complex transactions between related parties. Their

complexity and opaque nature can also increase the latitude for managers to shield managerial

diversion. As such, tax avoidance is most beneficial to firm value when the firm has strong

governance to mitigate the agency conflict and restrict managerial opportunism. For instance,

Desai and Dharmapala (2009) find tax avoidance is value-enhancing only for firms with

8 See http://www.sec.gov/Archives/edgar/data/14637/0001164073-02-000022.txt.

13

effective corporate governance (as proxied by high levels of institutional ownership). Wilson

(2009) shows that tax sheltering activities increase firm value (as indicated by abnormal returns)

only for firms with stronger shareholder rights. Since hedge fund activism results in an increase

in the strength of external monitoring of the target firm (Briggs 2007, Brav et al. 2008, Klein and

Zur 2009), we conjecture that the subsequent increase in tax avoidance should lead to an

improvement in firm value.

Hypothesis 2: The increase in tax avoidance in target firms after the activist hedge fund

intervention is associated with an increase in firm value.

II. Data and Primary Results

A. Sample Selection

Consistent with prior literature (e.g. Brav et al. 2008, Klein and Sur 2009, Cheng et al.

2010), our hedge fund sample is assembled from Schedule 13D filings. The 1934 Securities

Exchange Act requires investors who take a 5% or greater stake in a publicly traded firm file a

Schedule 13D with the SEC within 10 days and declare any intentions to influence the firm‟s

management.9 Material changes in a held position are reported using Schedule 13D/A. When a

hedge fund files form 13D with the SEC, it declares intent to influence firm management, and

accordingly we collect 13D filings by hedge funds to identify activism events.

We start our sample collection by obtaining all Schedule 13D and 13D/A filings between

January 1, 1994 and December 31, 2008 from the EDGAR database of the SEC. From each

filing we collect the filing date, the name of the filer, and the name of the identified target. We

then match the filers with a comprehensive list of hedge funds to identify Schedule 13D and

13D/A filings by hedge funds. We identify 435 activist hedge funds and 2,981 activist events in

9 When the investor has no intention to influence firm management, Schedule 13G is required instead of 13D.

14

the sample period spanning 1994-2008. We next collect additional information on the activist

events including hedge funds‟ objectives, tactics, and ownership levels in the target firm. We

also calculate the length of the holding period (investment horizon) from the initial 13D filing to

the filing of Schedule 13D/A that indicates hedge fund ownership falls below 5%.

Table I Panel A shows the distribution of hedge fund activist events by year. There is an

increasing trend in the number of hedge fund activist events over years with a spike (224) in

1997. In Panel B, we present the frequency of participation by hedge funds. A majority (60.69%)

of funds are involved in no more than three activist events in the sample period, while 14.94%

engage in more than ten activist events in the period. This suggests that while the majority of

hedge funds do not engage in activism on a regular basis, some do so frequently probably due to

the possible economic benefits or their expertise accumulated from repeated successful

interventions. In Panel C, we show the industry distribution of the target firms based on the Fama

and French 48-industry classification.10

Prior literature finds cross-industry variation in firms‟

effective tax rates, suggesting differences in levels of tax avoidance between firms may be

partially explained by industry differences. We thus include industry dummies in each of our

primary tests to control for industry effects.

B. Variable Construction and Descriptive Statistics

In addition to the hedge fund activism data, we obtain from Compustat the required

financial statement data, from Thomson‟s 13F database the institutional ownership data, and

from CRSP daily stock return data. A detailed definition of each variable used in our research

design appears in the Appendix.

10

The industry classification is downloaded from Prof. Ken French‟s website.

15

Hanlon and Heitzman (2010) prescribe caution when selecting measures of tax

avoidance. In particular, they note that each empirical metric computed from the financial

statements captures different aspects of a firm‟s tax strategy. As a result, the influence of tax

strategies such as those that permanently reduce tax liability (e.g., debt tax shields) versus those

that simply defer taxes to future periods (e.g., accelerated depreciation) cannot be consistently

reflected across the empirical measures. While we maintain our focus on tax avoidance, as

opposed to more extreme tax aggression, we make no formal hypotheses on the types or manner

of avoidance in which target firms are engaged. As such, we consider four broad constructs of

tax avoidance that are well established in the literature.

A firm‟s effective tax rate is a popular metric for evaluating a firm‟s ability to minimize

income taxes. We follow Chen et al. (2010) and compute an adjusted version of this metric, the

current effective tax rate (Current ETR), defined as a firm‟s total income tax expense (Compustat

#16) less deferred income tax expense (#50), divided by pretax net income (#170) less special

items (#17). Because Current ETR captures tax strategies that give rise to both permanent and

temporary book-tax differences through its exclusion of deferred tax expense, we regard it as a

suitable measure of tax avoidance in the context of hedge fund activism since funds might

benefit from tax deferral strategies in addition to tax elimination.11

A lower Current ETR

suggests the firm is paying a smaller portion of its pretax book profits to taxing authorities, and is

more effectively avoiding income taxes than firms with a higher Current ETR. Consistent with

prior literature (e.g. Chen et al. 2010, Baderstcher et al. 2009), we restrict Current ETR to [0, 1].

The Current ETR is expressed as the followings:

Current ETRi,t =

(Total Tax Expensei,t - Deferred Tax Expensei,t) / (Pretax Incomei,t

- Special Itemsi,t)

11

In untabulated analyses, we find our results are robust to inclusion of special items in the denominator, as well as

to using the overall ETR, including deferred tax expense in the denominator, in place of Current ETR.

16

Dyreng et al. (2008) propose an alternate version of the effective tax rate which uses the

actual cash taxes paid as disclosed on the statement of cash flows (#317) in the numerator while

retaining the traditional denominator. One advantage of this metric is it is independent of

statutory changes to differences in book and tax income, such as accounting for employee stock

options pre- and post-SFAS 123R, and its numerator is free from possible accrual manipulation

used to manage after-tax earnings.12

We include the cash effective tax rate (Cash ETR) as our

second measure of tax avoidance, and similarly limit Cash ETR to [0, 1]. The Cash ETR is

expressed as the following:

Cash ETRi,t =

Taxes Paidi,t / (Pretax Incomei,t - Special Itemsi,t)

Our two remaining measures are based on measures of book-tax differences. First, we

calculate the Manzon-Plesko (2002) book-tax difference (MP_BTD), which compares reported

domestic book income (#272) to the total of a firm‟s estimated domestic taxable income (#63

divided by the maximum statutory rate), state (#173) and other (#211) income tax expenses, and

equity contained in earnings (#55), scaled by lagged total assets (#6). The MP_BTD is expressed

as the followings:

MP_BTDi,t =

(Domestic Incomei,t - (Federal Income Tax Expensei,t/.35) - State Income

Tax Expensei,t - Other Income Tax Expensei,t - Equity Incomei,t) / (Total

Assetsi,t-1)

A positive value for MP_BTD suggests the firm underreports taxable income to the IRS

relative to its book income, and large values of the MP_BTD are indicative of greater levels of

tax avoidance. MP_BTD captures tax strategies that lead to both permanent and temporary

12

Both of our ETR metrics include pretax book income in the denominator, which is not free of the influence of

discretionary accruals. As noted by Hanlon and Heitzman (2010), conforming tax avoidance, or those strategies that

reduce both book and taxable income, are not captured in these measures. We address this concern in Section IV.E.

17

differences between book income and taxable income. Desai and Dharmapala (2006) note that

federal tax expense, used to estimate domestic income, is affected by income-changing

discretionary accruals used for earnings management purposes. To mitigate the influence of

earnings management strategies on book-tax differences, they propose an alternative book-tax

difference metric which is obtained by regressing MP_BTD on total accruals (TA) derived from

the cash flow method suggested by Hribar and Collins (2002): MP_BTDi,t = β1TAi,t + μi + εi,t.13

The residual of this regression (ε), expected to be largely free of earnings management (or at

least that attributable to accruals) is the Desai-Dharmapala book-tax difference (DD_BTD).

Similar to MP_BTD, larger values of DD_BTD imply greater levels of tax avoidance.14

C. Changes in Tax Avoidance following Hedge Fund Intervention

We employ both univariate and multivariate tests to examine the changes in tax

avoidance following hedge fund intervention.

C.1. Univariate Test

Table II presents mean levels of tax avoidance for target firms around hedge fund

activism events. For each measure, we present the raw and industry- adjusted averages from the

year prior to the activism event to the second year after the event (event year 0 being the year of

the intervention announcement). For each tax avoidance measure, we require a constant sample

with non-missing data across the event year window [-1, +2], and thus the sample size differs

across different tax avoidance measures. For the ETR measures in Panel A, we observe a

significant decrease over the period from one year prior to one year after the activism event for

13

μi is used to indicate the firm fixed-effect. 14

A comprehensive discussion of these and other tax avoidance measures can be found in Hanlon and Heitzman

(2010).

18

both Current ETR (-0.027) and Cash ETR (-0.032 ).15

This decrease is less pronounced when the

post-event period is extended to two years. The decrease in Current ETR (-0.028) is significant at

the 10% level, while the decrease (-0.014) in Cash ETR is no longer significant. In the second

column for each measure, we present industry-adjusted differences. For both Current ETR and

Cash ETR the differences between the year prior to the intervention and the year after (-0.029

and -0.039, respectively) are negative and significant. We find similar differences between the

year prior to the intervention and year t+2 for both Current ETR and Cash ETR (-0.035 and

-0.027, respectively). The univariate tests for both Current ETR and Cash ETR measures support

our first hypothesis, indicating increases in tax avoidance following hedge fund intervention.

In Table II Panel B, univariate results for the book-tax difference measures are opposite

in sign but generate similar inferences. For the unadjusted measures, there is a significant

increase in both MP_BTD (0.062) and DD_BTD (0.026) from the year immediately prior to the

hedge fund intervention and the year after. A similar significant increase is also observed for

year t+2 (0.076 and 0.024, respectively). The industry-adjusted measures show similar increases

in book-tax differences in both years following the intervention for both MP_BTD (0.069 and

0.087, respectively) and DD_BTD (0.025 and 0.019, respectively). Taken together, the

univariate results in Table II are consistent with an increase in tax avoidance following the hedge

fund activism event.

15

The raw levels of Current ETR and Cash ETR seem high. However, since both measures are winsorized at [0, 1],

outliers are not an issue. Furthermore, the adjusted levels of Current ETR and Cash ETR indicate that these levels

are only about 1.4 to 6.6 basis percentage points higher than the industry averages. We also estimate the association

between tax avoidance in t and the probability of being targeted by hedge fund activists in t+1, using logistic

regressions as in Table IV of Brav et al. (2008). We find these two ETR measures are positively associated with the

likelihood of being targeted but coefficient on the two BTD measures are insignificant. Therefore, there is some

evidence that tax inefficiencies (as indicated by high ETRs) could prompt interventions by hedge fund activists.

19

C.2. Multivariate Test

Our results in Table II could be driven by capital, operational, and performance changes

after the hedge fund intervention. Therefore, we conduct multivariate regressions and control for

common determinants of tax avoidance. We estimate the following Equation (1) cross-

sectionally for each of our tax avoidance measures. Tobit (OLS) regressions are used when the

dependent variables are Current ETR and Cash ETR (MP_BTD and DD_BTD), which are

truncated to [0, 1].

Tax Measurei,t =

α0 + β0 DYear0i,t + β1 DYear1i,t + β2 DYear2i,t + β3 ROEi,t+ β4 Leveragei,t

+ β5 ∆NOLi,t + β6 NOLi,t + β7 Foreign Incomei,t + β8 PPEi,t+ β9 Intangible

Assetsi,t + β10 Equity Incomei,t + β11 MTBi,t-1+ β12 Sizei,t-1 + Year

Dummies + Industry Dummies + εi,t (1)

Tax Measure,t is the firm‟s Current ETR, Cash ETR, MP_BTD, or DD_BTD in period t.

DYear0, DYear1, and DYear2 are dummy variables that equal one if the current year is the event

year 0, +1, and +2, respectively, and zero otherwise. For the ETR (BTD) measures, a negative

(positive) coefficient on DYear1 and DYear2 variables indicate higher levels of tax avoidance in

event year +1 and event year +2 relative to event year -1

We also include a number of control variables that have been shown by prior literature as

determinants of tax avoidance (e.g., Manzon and Plesko 2002, Mills 1998, Rego, 2003, Dyreng

et al. 2008, Frank et al. 2009, Chen et al. 2010). Return on equity (ROE) is calculated as

operating income scaled by the lagged book value of equity (#170-#192, scaled by #60), and

captures a firm‟s financial performance.16

To further control for prior operating loss

carryforwards which may reduce current period tax burdens, we follow Mills (1998) and include

∆NOL, the change in a firm‟s tax loss carryforward (#52) from the prior to current period, scaled

16

We use ROE, as opposed to return on assets (ROA), since the correlation between ROA and MP_BTD is more

than 80%.

20

by lagged total assets (#6). Firms with a decrease in their tax loss carryforwards potentially

exercised some of these tax benefits and reduced current period tax payments. Mills (1998) also

finds that the existence of a tax loss carryfoward in the financial statements is a reasonable proxy

for the existence of such exercisable benefits, so we include NOL, an indicator variable that

equals to one if the firm had a positive tax loss carryforward at the beginning of the year.

The variables Leverage, Foreign Income, PPE, Intangible Assets, and Equity Income

capture firm characteristics that by statute affect a firm‟s income tax liability. Since interest

expense is excluded from taxable income while dividend payments are not, a firm‟s capital

structure is an important determinant of its expected tax liability. The firm‟s Leverage (long term

debt, #9, scaled by lagged total assets, #6) is included to control for high levels of debt that

create tax benefits and thus influence our tax avoidance measures. Since generally foreign profits

are not subject to US tax until repatriated, we include Foreign Income, the firm‟s foreign income

scaled by lagged total assets (#273/lagged #6), to control for book income which may not result

in a current tax liability.17

A firm‟s book income generally differs from its tax income. For

instance, depreciation rules between book and tax are rarely equivalent, and thus firms with

higher levels of depreciable assets may exhibit greater book tax differences simply attributable to

heterogeneous statutory requirements. Accordingly, we include the firm‟s property, plant, and

equipment assets, PPE (#8/lagged #6) as an explanatory variable. Similarly, intangible assets and

equity earnings (recognized under the equity method) are subject to inconsistent book and tax

accounting rules, and inclusion of the variables Intangible Assets (intangible assets, #33, scaled

by lagged total assets, #6) and Equity Income (equity income in earnings, #55, scaled by lagged

17

Firms should recognize deferred tax expense on foreign earnings which are not considered permanently

reinvested, but minimal guidance in GAAP regarding the definition in “permanently reinvested” results in wide

variation in application of this rule in practice.

21

assets, #6) controls for variations in the tax measures due to these persistent sources of book-tax

differences.

The final control variables we include in our regressions are Size (natural logarithm of the

firm‟s market value of equity, #199 × #25) and MTB (market value of equity, #199 × #25, scaled

by book value of equity, #60), the former capturing the size and scale of the firm, and the latter

proxying for growth opportunities.

We include industry and year fixed effects to capture variations attributable to these

sources. After removing observations with missing values for the control variables or tax

avoidance metrics, our regression analysis is performed on 4,734 firm-years for the Current ETR

test, 4,847 for the Cash ETR test, 5,613 for the MP_BTD test, and 5,518 for the DD_BTD test.

We present descriptive statistics in Panel A of Table III. The mean (median) values for Current

ETR, Cash ETR, MP_BTD and DD_BTD are 0.456 (0.345), 0.493 (0.354), -0.185 (-0.019), and

0.028 (0.078), respectively. The seemingly large negative mean of MP_BTD (-0.185) is driven

by a few extreme observations, as the median (-0.019) is much smaller.18

We present Pearson

correlations in Panel B of Table III. As expected, these two ETR measures are significantly and

negatively correlated with the two BTD measures. Across all four tax avoidance measures,

higher levels of tax avoidance are positively correlated with ROE, Foreign Income, and Lagged

Size and negatively correlated with Change in NOL.

We present the results of the four cross-sectional regressions in Table IV. The results in

Panel A provide robust support for our first hypothesis. The coefficients on the dummy variables

for the year of the intervention (DYear0) are not significantly different from zero across all four

measures of tax avoidance The coefficients for the first year following the event (DYear1) are

18

We winsorize BTD measures at top and bottom 1%, but still have about 5% of observations with MP_BTD less

than -1.

22

negative and significant for Current ETR (-0.051) and Cash ETR (-0.084) and positive and

significant for MP_BTD (0.038) and DD_BTD (0.024), consistent with an increase in tax

avoidance in the post-intervention period. These increases in tax avoidance persist into the

second event year with unchanged signs and significant coefficients for DYear2 across all four

measures (-0.071 for Current ETR, -0.087 for Cash ETR, 0.034 for MP_BTD and 0.019 for

DD_BTD). DD_BTD loading positively in the years following the intervention suggests the

increase in avoidance is not due entirely to concurrent accruals-based earnings management,

which we discuss further in Section IV.E. The coefficients on control variables generally exhibit

signs consistent with our expectations. ROE and Size are consistently positively associated with

tax avoidance. Decreases in tax loss carryforwards (∆NOL) are positively associated with

avoidance, consistent with the use of these deferred tax assets to reduce current period liabilities.

Foreign Income and Equity Income are positively associated with avoidance as measured by the

ETRs, but show mixed signs for the BTD measures. This difference may be attributable to the

partial removal of tax-influencing accruals from DD_BTD and suggests that foreign income and

equity income both serve to reduce measured tax avoidance that is due mostly to tax strategies.

To check whether our results are driven by industry variation in tax treatments and

practices, we repeat our analysis in Panel A of Table IV by replacing the dependent variable in

Equation (1) with the corresponding industry-adjusted level of each tax measure. Specifically,

the raw levels of the tax measures are adjusted by the average levels of the firms in the same 2-

digit SIC industry in the same year. Panel B of Table IV presents the results of these regressions,

and our findings are generally robust. The coefficients on the dummy for the year of the

intervention are all insignificantly different from zero, while the coefficients on the dummy for

the year following the intervention (DYear1) are significantly negative for the adjusted Current

23

ETR (-0.035) and adjusted Cash ETR (-0.056) and significantly positive for the MP_BTD (0.029)

and DD_BTD (0.023). These increases in tax avoidance persist into the second year following

the activism event as evidenced by significant coefficients on DYear2 (-0.045 for Current ETR,

-0.055 for Cash ETR, 0.029 for MP_BTD and 0.018 for DD_BTD). In summary, the multivariate

tests in Table IV show that increases in tax avoidance following hedge fund interventions and the

results are not driven by industry differences.

III. Does the Increase in Tax Avoidance Improve Firm Value?

Building on the role of agency conflict in tax avoidance (Desai and Dharmapala 2009,

Chen et al. 2010, Badertscher et al. 2009) we assert that the shareholder monitoring role of

activist hedge funds improves corporate governance, which in turn mitigates potential rent

extraction by managers and reduce agency costs of tax avoidance. We formulate our second

hypothesis on the basis that if the increase in tax avoidance documented in our primary analysis

is accompanied by the improved corporate governance provided by the activist hedge funds‟

monitoring, the tax avoidance increase should improve firm value. We test this hypothesis

following Desai and Dharmapala‟s (2009) work on tax avoidance and firm value and we limit

our observations to those firm-years in the two years following a hedge fund activism event, as

our previous results indicate significant changes in tax avoidance start in year t+1. The

dependent variable in these tests is the change in the firm‟s value as measured by Tobin‟s Q,

calculated following Desai and Dharmapala as the sum of a firm‟s total assets (#6) plus the

market value of equity (#199 × #25) less the book value of equity (#60), scaled by total assets

(#6). The variable ∆Tobin’s Q is measured as the current period Tobin‟s Q less the value for

Tobin‟s Q in the year prior to the activist fund intervention (event year -1). Similarly, we

24

compute ∆Current ETR, ∆Cash ETR, ∆MP_BTD, and ∆DD_BTD as the change in the tax

measure from event year -1 to the current period. We estimate four OLS regressions as specified

by the following Equation (2), each using a different metric for the change in tax avoidance,

along with control variables known to influence firm value.

∆Tobin’s Qi,t =

α0+ β0 ∆Tax Measurei,t + β1 ∆MTBi,t-1 + β2 ∆Sizei,t-1 + β3 ∆Return

Volatilityi,t + β4 ∆ROEi,t + β5 ∆R&Di,t+ β6 ∆CAPXi,t+ β7 ∆Sales Growthi,t

+ β8 ∆Total Accrualsi,t + β9 ∆Institutional Ownershipi,t + β10 Dummy for

Missing Institutional Ownershipi,t + β11 Tobin’s Qi,t-1 + Year Dummies +

Industry Dummies + εi,t (2)

We also include a number of control variables that are common determinants of firm

value. The variables MTB, Size, and ROE are computed similarly as in Equation (1), and all

change variables are calculated relative to event year -1, the year before the activist hedge fund

intervention. Return volatility is the standard deviation of daily stock returns over the current

year and is included to capture changes in risk that affect firm value. R&D is the annual expense

for research and development (#46) scaled by lagged total assets (#6), and similarly, CAPX is the

annual capital expenditures (#128) scaled by lagged total assets. We include these two variables

of current investments in our regression to recognize their positive effects on firm value even

though they may not yet have yielded book assets on the balance sheet. Sales Growth (net sales,

#12, minus lagged #12, divided by lagged #12) and the change in total accruals (∆Total

Accruals), measured using the cash flow method following Hribar and Collins (2002), are also

included. We control for changes in institutional ownership and introduce a dummy variable

which acknowledges missing values in the data to avoid dropping an excessive number of

observations. We include this variable as a proxy for corporate governance, following Desai and

Dharmapala‟s (2009) evidence that firm value is increasing in tax avoidance only in the presence

of relatively strong corporate governance (as proxied by higher levels of institutional ownership).

25

Since corporate governance is not strictly a function of the hedge fund‟s monitoring presence,

including this variable allows us to control for other changes in the firm‟s governance. Finally,

we include the value of Tobin’s Q at event year -1 as a control variable to control for omitted

factors that persistently affect firm value and for the level of Tobin‟s Q before hedge fund

intervention.

Table V presents the results of estimating Equation (2) using OLS regression. The

coefficients on all four tax avoidance measures are significant and signed consistent with our

hypothesis that change in tax avoidance in these hedge fund activism-targeted firms is value-

increasing. The coefficients on both ∆Current ETR and ∆Cash ETR are negative and significant

(-0.18 and -0.206, respectively), while both ∆MP_BTD and ∆DD_BTD have significant positive

coefficients (0.541 and 0.937, respectively). These results are also economically significant. The

standardized coefficients (untabulated) for ∆Current ETR, ∆Cash ETR, ∆MP_BTD and

∆DD_BTD are -0.074, -0.091, 0.101, and 0.155, respectively.19

By comparison, the largest

standardized coefficients for the control variables are 0.122, 0.111, 0.103, and 0.192 in the four

regressions, respectively. Taken together, we conclude that tax avoidance seems to be valued by

shareholders in the presence of hedge fund activists, consistent with the increased monitoring

accompanied by the activism mitigating potential agency costs associated with tax avoidance.

IV. Robustness Tests

A. Long-term Changes in Tax Avoidance

We extend the univariate analyses in Table II to examine the long-term persistence of

changes in tax avoidance. Since requiring a constant sample across the long period from event

19

The standard deviation of the dependent variable, ∆Tobin’s Q, is 1.251 in our sample. Therefore, for instance,

when the tax avoidance is measured by Current ETR, the economic impact of one standard deviation decrease in

Current ETR is an increase of Tobin‟s Q by 0.09 (=0.074×1.251).

26

year -1 to +5 introduces a survivorship bias and significantly reduces our sample, we impose this

restriction only on this robustness check.20

In Panel A of Table VI, we find that the decreases in

effective tax rate in general seem to persist in the long-run across the ETR measures of tax

avoidance. For instance, for the unadjusted measures, the change from event year -1 to event

year +5 is -0.087 for the Current ETR and -0.041 for the Cash ETR, respectively. The preceding

significant result is confirmed by the industry-adjusted Current ETR (change = -0.078), even

though this is not the case for industry-adjusted Cash ETR (change = -0.019). Results for the

BTD measures, in Panel B of Table VI, also suggest that the increases in book-tax difference

persist in the long run. Through event year +4, four years after the hedge fund intervention, the

increases in book-tax difference are still significant for both the unadjusted measures and

industry-adjusted measures (0.125 for MP_BTD, 0.118 for adjusted MP_BTD, 0.049 for

DD_BTD, and 0.033 for adjusted DD_BTD). The increases in MP_BTD fade out by the end of

event year +5, but the increases in DD_BTD, which is designed to eliminate the majority of

BTDs generated by concurrent earnings management, persist through event year +5 for both the

raw measure (0.048) and the industry adjusted level (0.026). In summary, results in Table VI

show that in general the changes in tax avoidance after hedge fund intervention persist and do

not fully reverse in the long run, indicating that hedge fund intervention influences target firms‟

long-term tax planning. Results also suggest that this long-term effect is more pronounced for

those tax savings that arise from tax planning (which decreases the numerator in the ETR

measures) and not through earnings manipulation (which inflates the denominator).

20

Results are similar if we do not impose the requirement of a constant sample.

27

B. Impact of Hedge Fund Influence on the Association between Tax Avoidance and Firm Value

It is likely that once hedge funds exit from the target firm, they either stop their

intervention efforts, or no longer have significant influence over the firm. Therefore, we test

whether changes in tax avoidance increase firm value only when hedge fund activists maintain

significant influence over the target firms. Following Brav et al. (2008), we define an exit as

hedge fund activists‟ ownership falling below 5% and classify firm-years as without hedge fund

influence if the hedge funds have exited from the firm. We use Equation (2) as in Table V and

extend the event window to [+1, +5] to increase the sample size for the exit subsample.21

Panel A

and B of Table VII show that the estimated coefficients for changes in four tax avoidance

measures for the subsamples of firm-years with and without hedge fund influence, respectively.

Similar to Table V, we find significant results in Panel A for all four measures, indicating that

increases in tax avoidance are associated with increases in target firms‟ value (-0.156 for

∆Current ETR, -0.184 for ∆Cash ETR, 0.339 for ∆MP_BTD, and 0.476 for ∆DD_BTD). On the

other hand, in Panel B, only ΔCash ETR has a significant coefficient (-0.174). The results thus

support the proposition that the value of tax avoidance, as documented in this study, is a function

of hedge fund monitoring. Though we document long-term changes in tax avoidance after hedge

fund intervention, the continuing presence of hedge fund activists appears to be a requirement for

the tax avoidance to improve firm value. Results in Table VII further confirm our conjecture that

informed monitoring provided by hedge fund activists mitigates rent extraction and increases the

net benefits of tax avoidance activities.

21 The sample size would otherwise be too small (only around 300 observations) if we use the event window [+1,

+2], and the lack of significant associations might be caused by a lack of statistical power. Our results are

qualitatively similar if we use year +3 or +4 as the ending year.

28

29

C. Are Target Firms’ Greater Tax Savings Driven by an Increased Use of Tax Sheltering?

We further analyze whether the increase in tax avoidance in target firms is driven by

firms‟ increased use of high-risk and potentially illegal tax planning strategies such as tax

sheltering.22

The costs and benefits to engaging in a tax shelter are a frequent subject of interest

in the literature. Graham and Tucker (2006) find that firms engaging in shelters use less debt,

suggesting that tax shelters serve as a substitute for the tax savings from debt financing. Hanlon

and Slemrod (2009) find a negative stock price reaction immediately following public revelation

of a firm‟s involvement in a tax shelter. Since the increased monitoring by hedge funds mitigates

the agency problem associated with tax avoidance and tax shelters are an extreme form of

avoidance lies beyond the optimal level of tax avoidance, we do not expect the target firms in our

sample are more likely to participate in shelters. Since hedge funds are sophisticated investors

with undiversified portfolios, they are less likely to seek risky strategies that might significantly

reduce the target firm‟s value (Kahan and Rock 2007, Cheng et al. 2010). Hedge funds‟ ability to

mitigate agency costs also reduces the possibility that managers engage in tax sheltering for the

sake of extracting private benefits. Wilson (2009) develops a model of firm characteristics to

predict the probability that a firm is likely currently engaging in tax sheltering. Using Wilson‟s

(2009) sheltering model, we examine whether hedge fund activism is associated with higher

probabilities of tax sheltering behaviors.23

Untabulated results show no evidence that target firms

22

There is no widely accepted definition of tax sheltering, but in our context we consider tax shelters to be

transactions initiated with the primary intention to avoid taxation of income, an aggressive form of avoidance that is

beyond the optimal level of avoidance for shareholders. Bankman (1999) shrewdly notes that “a tax shelter can be

defined as a product whose useful life is apt to end soon after its discovery by the Treasury.” 23

Even though the use of tax sheltering might be pervasive, sheltering activities are notoriously difficult to detect

(e.g., Graham and Tucker 2006). Academic studies on tax sheltering (Desai and Dharmapala 2006, Graham and

Tucker 2006, Wilson, 2009) usually rely on court documents and press reports to identify tax shelter firms and the

samples tend to be small. For instance, Wilson (2009) identifies only 59 shelter firms between 1975 and 2007.

30

are more likely to engage in tax sheltering after hedge fund intervention.24

Our results, therefore,

suggest that the greater tax savings achieved by target firms likely result from more efficient tax

planning rather than the use of egregious and risky tax evasion strategies, consistent with the

agency perspective and theorized optimal level of tax avoidance from the shareholder

perspective.25

D. Temporary or Permanent Tax Avoidance?

Both the current effective tax rate (Current ETR) and the Manzon-Plesko (2002) book-tax

difference (MP_BTD) capture tax strategies that give rise to both permanent and temporary

book-tax differences. One possible explanation for our findings is that targeted firms utilize tax

strategies that create temporary BTDs to shift tax burdens to future periods. In untabulated

analyses, we examine two other measures of book-tax differences, temporary differences

(deferred tax expense, #63, scaled by the statutory tax rate) and permanent differences

(calculated as total book-tax differences less temporary differences) as suggested by Frank et al.

(2009). We find significant increases in permanent book-tax differences and significant

decreases in temporary differences following the intervention, which indicate that our results are

not driven by temporary deferrals of tax burdens to future periods.

24

The univariate event-study analysis shows a slight decrease (about 1.9%) in the average industry-adjusted

estimated sheltering probability for target firms after the intervention. After controlling for firm characteristics, the

changes in the sheltering probabilities become insignificant in multivariate regressions. 25

Our ability to make inferences is limited by the extent to which Wilson‟s model captures the profile of the broader

set of tax shelter participants.

31

E. Does the Increase in Tax Avoidance Result from an Increase in Financial Reporting

Aggressiveness?

The academic and practitioner accounting literature (e.g., Revsine et al. 1999, Palepu et

al. 1996, Penman 2001) has long suggested that book-tax differences are an artifact of earnings

management, since the tax code generally allows for less managerial discretion through accruals

than GAAP. Frank et al. (2009) find a positive association between aggressive financial

reporting (inflating reported income) and aggressive tax reporting (reducing taxable income), and

intuitively in the presence of both types of aggressive reporting relatively large book-tax

differences will be observed. As a robustness check, we consider whether our results are driven

by concurrent earnings management that inflates reported income as opposed to non-conforming

tax avoidance. Our use of the Desai-Dharmapala (2006) residual book-tax difference (DD_BTD)

should alleviate this concern as this measure is intended to at least partially eliminate the book-

tax gap caused by earnings management. We nevertheless conduct two additional tests

(untabulated). First, we include total accruals (or discretionary accruals) in our baseline

regressions (Equation (1)), and we continue to find a significant increase in tax avoidance in the

post-intervention period. Second, we examine the changes in discretionary accruals after the

hedge fund intervention and do not find evidence of increases in earnings management. In

addition, a contemporaneous working paper, Cheng et al. (2010), documents an increase in

conservatism after the intervention (i.e., a decrease in financial reporting aggressiveness).

Therefore, we conclude that our findings are not driven by increased financial reporting

aggressiveness and earnings management in target firms.

32

F. Alternative Control Sample of Non-target Firms

In addition to the industry-control-group matching, we also use propensity score

matching to construct a control sample of non-target firms and then compute the differences in

tax avoidance measures between target firms and non-target firms.26

Specifically, we identify a

control firm for each target firm based on the closest propensity score, which is the predicted

probability of becoming a hedge fund activism target in the next year. The propensity score is

estimated from a logistic regression model as in Table IV of Brav et al. (2008) in which a

dummy variable of being targeted by hedge funds is regressed on the lagged values of firm size,

Tobin‟s Q, sales growth, return on assets, debt-to-equity ratio, annual dividend yield, R&D

expense, Herfindahl index, the number of analysts following, institutional ownership, and year

dummies. We estimate this logistic regression using all firms in the Compustat database with

available data from 1994 to 2008 and then use the obtained coefficients to estimate the

propensity score for each firm. Results from this propensity score matching procedure

(untabulated) are similar to those reported.

G. Other Robustness Checks

In unreported analyses, we also control for potential changes in external monitoring by

institutional ownership and auditors around hedge fund intervention. Specifically, we include the

level of institutional ownership and a dummy variable that equals one if the target firm used a

Big 6 auditor for the period. Our results are robust to these additional controls.

Finally, to minimize survivorship bias we use the event window [-1, +2] in our tabulated

analyses. One potential limitation with this approach arises from possible changes in tax strategy

26

Propensity score matching is a widely-used method to deal with selection bias and measures the “treatment effect”

as the outcome for the treated firm minus the outcome for an untreated firm with equal treatment probability (e.g., Li

and Prabhala 2007).

33

in the period prior to the intervention, as firm management may suspect a future activism event.

To control for this possibility, we extend the event window from years [-1, +2] to years [-2, +2]

in applicable tests (untabulated) and our conclusions are unaltered.

V. Discussion and Conclusion

This paper extends the literature of tax avoidance by examining a unique class of

shareholders, activist hedge funds, and testing whether their monitoring and intervention result in

increased levels of tax avoidance and increased firm value. We find significant increases in

avoidance in the target firms, as measured by both effective tax rates (ETRs) and book-tax

differences (BTDs), following activist funds‟ interventions. We also find that this change in tax

avoidance leads to an increase in firm value, suggesting that the increased monitoring by the

hedge fund activists plays an important role in the markets‟ valuation of tax avoidance. Our

evidence also shows that these increases in avoidance do not fully reverse in the long-run

(specifically five years after the activist fund intervention). However, these increases improve

firm value only when hedge fund activists have significant influence over target firms, providing

a direct linkage between hedge fund monitoring and value implications of tax avoidance. Our

results also suggest the greater tax savings achieved by target firms likely result from more

efficient tax planning rather than the use of tax sheltering, earnings management or temporary

tax deferrals.

A common criticism of hedge fund activists is that they pursue short-term profits at the

expense of long-term firm value. In this view, our evidence of increases in tax avoidance

following the intervention could simply be an artifact of tax strategies used to inflate hedge

funds‟ short-term profits. Two of our findings, however, refute this position in our context. First,

we find no significant increase in the probability a targeted firm engages in tax sheltering (an

34

aggressive form of tax avoidance). When considering using tax shelters, a firm must weigh the

short-term tax benefits (e.g., increased net income and free cash flow) against the long-term

expected legal costs and reputation damages (Chen et al. 2010). If activist funds are concerned

mainly with short-term performance, we expect that they would heavily discount these future

expected costs and enter into sheltering arrangements frequently. However, in Section IV.C, we

do not find increases in sheltering activities after hedge fund intervention. Second, short-termism

suggests that hedge funds should be more likely to push for strategies that create temporary

book-tax differences rather than permanent differences. Again, as shown in Section IV.D, we do

not find this to be the case.27

Our study contributes to the literature on several fronts. We find that tax avoidance level

is increasing in targeted firms following activist hedge fund intervention in a change analysis.

We also present robust evidence that increased tax avoidance accompanied by strengthened

monitoring is value enhancing. Our results confirm that the value-implication of tax avoidance is

a function of governance strength (Chen and Chu 2005, Crocker and Slemrod 2005, Desai and

Dharmapala 2006, 2009), and provide additional support for the validity of analyzing firm tax

strategy in an agency framework. In addition, we establish a direct linkage between increases in

tax avoidance following hedge fund intervention and increases in firm value, and identify

improving tax planning as a specific tactic through which hedge fund intervention adds to firm

value. Finally, our study suggests that hedge fund activists provide firms with motivation and

expertise to improve their tax strategies, thereby highlighting the importance of ownership

structure on corporate tax policies.

27

There are a number of other factors that might explain why short-termism does not manifest itself in our results.

First, hedge fund activists‟ future successes depend on its reputation (Zur 2010). Second, hedge funds have

relatively undiversified portfolios (Kahan and Rock 2007) and thus cannot afford to take legal and financial risks on

an individual firm. Finally, non-aggressive tax planning yields sufficient value improvements that reduce the need to

resort to aggressive tax strategies.

35

Our study has a few limitations that could be addressed in future research. Even though

we employ multiple tax avoidance measures to examine the impact of hedge fund intervention on

tax avoidance, we do not identify the specific strategies through which hedge funds are able to

increase tax avoidance in target firms. These strategies can take the form of financial strategies

such as employing additional debt, accounting strategies such as accelerating depreciation, and

operating strategies such as restructuring. In addition, although we document that increased tax

avoidance is associated with a contemporaneous increase in firm value, our test is nevertheless a

short-window analysis and future studies can further explore the impact of hedge fund activism

on long-term firm value.

36

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39

Appendix A

Variable Definition

Measures of Tax Avoidance

Current ETR

Current effective tax rate, which equals total income tax expense (#16)

minus deferred income tax expense (#50), divided by pretax net income

(#170) minus special items (#17) in year t. We truncate the values at 0

and 1.

Cash ETR Cash effective tax rate, which equals cash taxes paid (#317), divided by

pretax net income (#170) minus special items (#17) in year t. We truncate

the values at 0 and 1.

MP_BTD

Manzon-Plesko (2002) book-tax difference, which equals U.S. domestic

income (#272) minus U.S. domestic taxable income minus state income

taxes (#173) minus other income taxes (#211) minus equity in earnings

(#55), scaled by lagged assets (#6). U.S. domestic taxable income is

estimated as the current federal tax expense (#63) divided by the statutory

maximum corporate tax rate.

DD_BTD

Desai-Dharmapala (2006) residual book-tax difference, which equals the

residual from the following firm fixed-effect regression: BTi,t = β1TAi,t +

μi + εi,t, where BT is the Manzon-Plesko book-tax difference, TA is total

accruals measured using the cash flow method per Hribar and Collins

(2002). Both variables are scaled by lagged total assets and are winsorized

at 1% and 99% levels for regression purposes.

Hedge Fund Activism Variables

Dummy for Year t One if the current year is the event year t, with year 0 being the year in

which hedge fund activism is initiated, zero otherwise.

Governance Dummy One if the activists target the firm‟s corporate governance (board

independence, management change, managerial compensation, etc.), zero

otherwise.

Efficiency Dummy One if the activists target the firm‟s operational efficiency, zero

otherwise.

Sale of Target Dummy One if the activists attempt to force a sale of the target firm, zero

otherwise.

Maximum Ownership Maximum stock ownership of hedge fund activists during the holding

period.

40

Control Variables for Tax Avoidance Regressions

ROE Return on equity, measured as operating income (#170 - #192), scaled by

lagged book value of equity (#60).

Leverage Long-term debt (#9), scaled by lagged assets (#6).

Dummy for Positive Lagged

NOL Indicator variable coded as 1 if loss carry forward (#52) is positive at the

beginning of the year.

NOL Change in loss carry forward (#52), scaled by lagged assets (#6).

Foreign Income Foreign income (#273), scaled by lagged assets (#6).

PPE Property, Plant and Equipment (#8), scaled by lagged assets (#6).

Intangible Asset Intangible assets (#33), scaled by lagged assets (#6).

Equity Income Equity Income in earnings (#55), scaled by lagged assets (#6).

Lagged Market to book Market to book ratio at the beginning of the year, measured as market

value of equity (#199 × #25), scaled by book value of equity (#60).

Lagged Size Natural logarithm of market value of equity (#199 × #25) at the beginning

of the year.

Additional Variables for Tobin’s Q Regressions

Tobin‟s Q Total assets (#6) + market value of equity (#199 × #25) - book value of

equity (# 60)]/total assets (#6).

Return Volatility The standard deviation of daily stock returns over the current year.

R&D R&D expense (#46), scaled by lagged assets (#6).

CAPX Capital Expenditure (#128), scaled by lagged assets (#6).

Sales Growth The growth rate of sales over the previous year: Sales (#12) minus lagged

sales, scaled by lagged sales

Total Accruals Total accruals measured using the cash flow method per Hribar and

Collins (2002): Income before extraordinary items (#123) less cash flows

from operations less cash flows from extraordinary items(#308-#124).

Institutional Ownership The proportion of shares held by institutions.

41

Table I

Descriptive Statistics on the Hedge Fund Activism Sample

The sample consists of 2,981 hedge fund activist events initiated from 1994 to 2008. Panel A

presents the frequency of activist events by years. Panel B shows the participation frequency

of hedge fund activists. Panel C shows the industry distribution of sample firm-years (per

Fama and French 48 Industry Classification).

Panel A: Number of hedge fund activist events by year of first SC 13D filing

Year Frequency Percent

1994 12 0.40

1995 40 1.34

1996 109 3.66

1997 224 7.51

1998 169 5.67

1999 151 5.07

2000 168 5.64

2001 147 4.93

2002 154 5.17

2003 194 6.51

2004 221 7.41

2005 346 11.61

2006 373 12.51

2007 384 12.88

2008 289 9.69

Total 2,981 100

Panel B: Participation frequency of hedge fund activists

Number of

Events

Number of

Activists Percent

1 150 34.48

2 72 16.55

3 42 9.66

4 22 5.06

5 22 5.06

6 18 4.14

7 16 3.68

8 12 2.76

9 12 2.76

10 4 0.92

>10 65 14.94

Total 435 100

42

Table I - Continued

Panel C: Industry distribution of sample firm-years (per Fama and French 48 Industry Classification)

Industry Name

# of

Obs. Percent Industry Name

# of

Obs. Percent

Agriculture 11 0.37

Shipbuilding, Railroad

Equipment 8 0.27

Food Products 42 1.41 Defense 6 0.20

Candy & Soda 6 0.20 Precious Metals 6 0.20

Beer & Liquor 3 0.10

Non-Metallic and Industrial

Metal Mining 15 0.50

Tobacco Products 4 0.13 Coal 13 0.44

Recreation 24 0.81 Petroleum and Natural Gas 96 3.22

Entertainment 55 1.85 Utilities 51 1.71

Printing and Publishing 33 1.11 Communication 112 3.76

Consumer Goods 55 1.85 Personal Services 46 1.54

Apparel 42 1.41 Business Services 398 13.35

Healthcare 58 1.95 Computers 96 3.22

Medical Equipment 118 3.96 Electronic Equipment 134 4.50

Pharmaceutical Products 135 4.53

Measuring and Control

Equipment 46 1.54

Chemicals 42 1.41 Business Supplies 29 0.97

Rubber and Plastic Products 34 1.14 Shipping Containers 5 0.17

Textiles 14 0.47 Transportation 43 1.44

Construction Materials 57 1.91 Wholesale 115 3.86

Construction 31 1.04 Retail 180 6.04

Steel Works Etc 38 1.27 Restaurants, Hotels, Motels 62 2.08

Fabricated Products 7 0.23 Banking 209 7.01

Machinery 74 2.48 Insurance 84 2.82

Electrical Equipment 47 1.58 Real Estate 36 1.21

Automobiles and Trucks 32 1.07 Trading 193 6.47

Aircraft 5 0.17 Almost Nothing 31 1.04

43

Table II

Descriptive Statistics on Changes in Tax Avoidance after Hedge Fund Intervention

This table reports the mean levels of tax avoidance for target firms around hedge fund activist events from

event year -1 to event year +2 with event year 0 being the year of the intervention announcement. For each

tax avoidance measure, we require a constant sample with non-missing data across the event window [-1, +2].

Industry adjusted tax avoidance measures are adjusted by the average levels of the firms in the same 2-digit

SIC industry in the same year. *, **, and *** indicate statistical significance at the 10%, 5%, and 1% levels

(one-sided), respectively. The Appendix has the variable definitions.

Panel A: Effective Tax Rate Measures

Current ETR Cash ETR

Level Adj. Level Level Adj. Level

Year -1 0.442 0.049*** 0.475 0.066*** Year 0 0.438 0.042*** 0.467 0.053***

Year +1 0.415 0.019* 0.443 0.028**

Year +2 0.415 0.014 0.462 0.040***

(Year +1) – (Year -1) -0.027** -0.029** -0.032** -0.039**

(Year +2) – (Year -1) -0.028* -0.035** -0.014 -0.027*

No. of Observations 621 621 713 713

Panel B: Book-Tax Difference Measures

MP_BTD DD_BTD

Level Adj. Level Level Adj. Level

Year -1 -0.203 -0.006 0.012 -0.002

Year 0 -0.171 0.032 0.025 0.011

Year +1 -0.140 0.063*** 0.037 0.023***

Year +2 -0.127 0.081*** 0.036 0.017**

(Year +1) – (Year -1) 0.062** 0.069*** 0.026*** 0.025***

(Year +2) – (Year -1) 0.076*** 0.087*** 0.024** 0.019**

No. of Observations 878 878 831 831

44

Table III

Descriptive Statistics and Correlations

This table presents descriptive statistics and Pearson correlations for the sample that includes firm-years

of target firms in the event window [-1, +2] with required data, where event year 0 is the year of the

intervention announcement. In Panel B, p-values are reported in parentheses. The Appendix has the

variable definitions.

Panel A: Descriptive Statistics

Variable N Mean Std 5% 25% Median 75% 95%

Tax Avoidance

Measures

Current ETR 4,734 0.456 0.383 0.000 0.116 0.345 1.000 1.000

Cash ETR 4,847 0.493 0.402 0.000 0.124 0.354 1.000 1.000

MP_BTD 5,613 -0.185 0.831 -0.780 -0.129 -0.019 0.018 0.107

DD_BTD 5,518 0.028 0.259 -0.414 -0.007 0.078 0.144 0.288

Control

Variables

ROE 6,418 -0.117 1.650 -1.646 -0.254 0.029 0.207 0.915

Leverage 6,418 0.237 0.333 0.000 0.001 0.122 0.347 0.849

Dummy for

Lagged NOL 6,418 0.454 0.498 0.000 0.000 0.000 1.000 1.000

Change in NOL 6,418 0.076 0.411 -0.137 0.000 0.000 0.027 0.603

Foreign Income 6,418 0.003 0.026 -0.019 0.000 0.000 0.000 0.047

PPE 6,418 0.267 0.295 0.014 0.073 0.173 0.354 0.832

Intangible Asset 6,418 0.175 0.280 0.000 0.000 0.063 0.250 0.653

Equity Income 6,418 0.000 0.004 -0.001 0.000 0.000 0.000 0.003

Lagged Market

to Book 6,418 2.236 5.342 -1.838 0.843 1.593 2.903 9.129

Lagged Size 6,418 4.813 1.824 1.842 3.601 4.736 6.093 7.869

45

Table III – Continued

Panel B: Correlations

A B C D E F G H I J K L M N

Current ETR A 1.000

Cash ETR B 0.860 1.000

(0.000)

MP_BTD C -0.287 -0.259 1.000

(0.000) (0.000)

DD_BTD D -0.234 -0.230 0.607 1.000

(0.000) (0.000) (0.000)

ROE E -0.141 -0.163 0.070 0.136 1.000

(0.000) (0.000) (0.000) (0.000)

Leverage F -0.029 -0.040 -0.112 0.100 0.009 1.000

(0.049) (0.006) (0.000) (0.000) (0.478)

Dummy for

Lagged NOL G 0.049 0.036 -0.011 0.012 -0.006 -0.004 1.000

(0.001) (0.011) (0.392) (0.377) (0.626) (0.761)

Change in NOL H 0.128 0.114 -0.241 -0.218 -0.041 0.051 0.076 1.000

(0.000) (0.000) (0.000) (0.000) (0.001) (0.000) (0.000)

Foreign Income I -0.168 -0.200 0.046 0.007 0.064 0.028 -0.021 -0.060 1.000

(0.000) (0.000) (0.001) (0.605) (0.000) (0.026) (0.092) (0.000)

PPE J -0.066 -0.089 -0.041 0.149 0.017 0.444 -0.077 0.049 0.050 1.000

(0.000) (0.000) (0.002) (0.000) (0.178) (0.000) (0.000) (0.000) (0.000)

Intangible Asset K -0.016 -0.046 -0.061 0.064 -0.008 0.319 0.061 0.083 0.046 0.013 1.000

(0.282) (0.001) (0.000) (0.000) (0.519) (0.000) (0.000) (0.000) (0.000) (0.295)

Equity Income L -0.081 -0.090 0.022 -0.008 0.031 0.003 -0.034 -0.050 0.036 0.007 -0.029 1.000

(0.000) (0.000) (0.099) (0.566) (0.013) (0.802) (0.006) (0.000) (0.004) (0.554) (0.022)

Lagged Market

to Book M -0.057 -0.035 -0.027 -0.115 -0.368 -0.060 -0.006 -0.019 0.002 -0.003 0.004 -0.015 1.000

(0.000) (0.014) (0.045) (0.000) (0.000) (0.000) (0.641) (0.133) (0.879) (0.784) (0.770) (0.224)

Lagged Size N -0.114 -0.170 0.227 0.196 0.057 0.080 0.020 -0.118 0.149 0.062 0.134 0.007 0.133 1.000

(0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.115) (0.000) (0.000) (0.000) (0.000) (0.557) (0.000)

46

Table IV

Multivariate Analysis of Changes in Tax Avoidance

after Hedge Fund Intervention

This table presents the results on changes in tax avoidance of target firms around hedge fund activist events. The

sample includes firm-years of target firms in the event window [-1, +2] with required data, where event year 0 is

the year of the intervention announcement. Tobit regressions are used when the dependent variables are Current ETR and Cash ETR. Panel A and Panel B show the results from unadjusted and industry adjusted tax avoidance

measures, respectively. Industry adjusted tax avoidance measures are adjusted by the average levels of the firms

in the same 2-digit SIC industry in the same year. Both industry and year dummies are included. t-statistics

reported in parentheses are based on robust standard errors. *, **, and *** indicate statistical significance at the

10%, 5%, and 1% levels. The Appendix has the variable definitions.

Panel A: Unadjusted Tax Avoidance Measures

Dependent Variable:

Current ETR

Cash ETR

MP_BTD

DD_BTD

Dummy for Year 0 -0.012 -0.020 0.009 0.005

(-0.55) (-0.83) (0.77) (0.56)

Dummy for Year +1 -0.051** -0.084*** 0.038*** 0.024***

(-2.15) (-3.35) (3.35) (2.60)

Dummy for Year +2 -0.071*** -0.087*** 0.034*** 0.019**

(-2.82) (-3.21) (2.69) (2.03)

Control Variables:

ROE -0.069*** -0.080*** 0.032*** 0.013***

(-5.63) (-6.38) (4.40) (3.22)

Leverage 0.042 0.068 -0.035 0.032

(1.10) (1.54) (-1.11) (1.59)

Dummy for Positive 0.065*** 0.074*** -0.009 0.014**

Lagged NOL (3.59) (3.85) (-1.02) (2.06)

NOL 0.264*** 0.247*** -0.244*** -0.107***

(5.61) (4.51) (-8.25) (-5.72)

Foreign Income -3.321*** -4.020*** 0.307* -0.454***

(-10.10) (-11.84) (1.83) (-3.62)

PPE -0.158*** -0.161*** -0.039 0.060**

(-3.31) (-3.02) (-0.95) (2.33)

Intangible Asset -0.056 -0.114** 0.025 0.048**

(-1.38) (-2.54) (0.72) (2.14)

Equity Income -12.244*** -14.931*** 2.692** -1.901**

(-4.72) (-5.69) (2.12) (-2.42)

Lagged Market -0.002 0.001 -0.004*** -0.003***

to Book (-0.85) (0.41) (-2.98) (-2.91)

Lagged Size -0.031*** -0.063*** 0.040*** 0.025***

(-5.72) (-10.76) (10.16) (10.48)

Constant 0.866*** 0.914*** 0.032*** -0.152**

(4.17) (3.90) (4.40) (-2.13)

No. of Observations 4,734 4,847 5,613 5,518

Pseudo/Adj. R2 0.083 0.098 0.249 0.197

47

Table IV- Continued

Panel B: Industry-Adjusted Measures of Tax Avoidance

Dependent

Variable:

Adj.

Current ETR

Adj.

Cash ETR

Adj.

MP_BTD

Adj.

DD_BTD

Dummy for Year 0 -0.009 -0.015 0.013 0.004

(-0.63) (-1.08) (1.02) (0.46)

Dummy for Year +1 -0.035** -0.056*** 0.029** 0.023**

(-2.34) (-3.64) (2.27) (2.38)

Dummy for Year +2 -0.045*** -0.055*** 0.029** 0.018*

(-2.80) (-3.32) (2.15) (1.88)

Control Variables:

ROE -0.034*** -0.037*** 0.028*** 0.013***

(-5.96) (-6.92) (4.12) (3.13)

Leverage 0.012 0.039 -0.050 0.030

(0.52) (1.51) (-1.61) (1.50)

Dummy for

Lagged NOL 0.033*** 0.025** -0.009 0.012*

(2.88) (2.12) (-0.98) (1.78)

Change in NOL 0.151*** 0.118*** -0.264*** -0.107***

(6.78) (4.92) (-8.36) (-5.75)

Foreign Income -1.966*** -2.211*** 0.067 -0.504***

(-10.17) (-11.95) (0.36) (-3.96)

PPE -0.082*** -0.074** 0.009 0.066**

(-2.80) (-2.27) (0.22) (2.57)

Intangible Asset -0.038 -0.067** 0.027 0.050**

(-1.52) (-2.49) (0.85) (2.28)

Equity Income -7.553*** -9.026*** 2.813** -1.258

(-4.61) (-5.72) (2.03) (-1.60)

Lagged Market

to Book -0.002 -0.001 -0.003** -0.003***

(-1.54) (-0.60) (-2.20) (-2.62)

Lagged Size -0.021*** -0.036*** 0.044*** 0.025***

(-6.06) (-10.42) (10.62) (10.50)

Constant 0.269** 0.353** -0.161 -0.160**

(2.16) (2.30) (-1.54) (-2.12)

No. of Observations 4,734 4,845 5,613 5,518

Adj. R2 0.109 0.124 0.220 0.100

48

Table V

Does the Increase in Tax Avoidance Improve Firm Value? This table presents the results on the impact of changes in target firms‟ tax avoidance on changes in their firm

values around hedge fund activist events. The sample includes firm-years of target firms in the event window

[+1, +2] with required data, where event year 0 is the year of the intervention announcement. Changes in

Tobin‟s Q, tax avoidance measures, and control variables are computed relative to the levels in year -1. Also

included in the regressions are year and industry fixed effects dummies. t-statistics reported in parentheses are

based on robust standard errors. *, **, and *** indicate statistical significance at the 10%, 5%, and 1% levels.

The Appendix has the variable definitions.

Dependent Variable: Tobin‟s Q

Current ETR -0.180***

(-3.20)

Cash ETR -0.206***

(-4.59)

MP_BTD 0.541**

(2.25)

DD_BTD 0.937***

(3.33)

Control Variables:

Lagged Book -0.033*** -0.029*** -0.028** -0.053**

to Market (-3.53) (-3.12) (-2.41) (-2.43)

Lagged Size 0.138*** 0.121*** 0.088 0.063

(3.46) (3.37) (1.58) (1.09)

Return Volatility 4.388*** 3.294* -0.674 -0.857

(2.60) (1.87) (-0.28) (-0.36)

ROE 0.029** 0.021*** -0.014 -0.021

(2.50) (2.86) (-0.55) (-0.79)

R&D 2.125** 0.874 2.058 2.403*

(2.05) (1.11) (1.63) (1.88)

CAPX 0.125 0.396 1.146*** 1.442***

(0.32) (0.89) (2.77) (3.43)

Sales Growth 0.102** 0.046 -0.022 -0.041

(2.51) (0.97) (-0.46) (-0.82)

Total Accruals -0.100 -0.062 0.316 1.327***

(-0.38) (-0.29) (1.10) (3.75)

Institutional

Ownership 0.873*** 0.712*** 0.883*** 0.808***

(3.21) (2.89) (3.06) (2.80)

Dummy for missing 0.039 -0.017 0.025 0.039

Institutional

Ownership (0.77) (-0.34) (0.32) (0.51)

Tobin‟s Q in Year -1 -0.527*** -0.612*** -0.496*** -0.459***

(-8.64) (-14.09) (-6.35) (-5.47)

Constant 1.156* 1.306* 1.316** 1.296**

(1.78) (1.93) (2.01) (2.04)

No. of Observations 1,095 1,229 1,355 1,335

Adj. R2 0.394 0.464 0.251 0.225

49

Table VI

Long-Term Changes in Tax Avoidance after Hedge Fund Intervention

This table reports the mean levels of tax avoidance for target firms around hedge fund activist events from

event year -1 to event year +5 with event year 0 being the year of the intervention announcement. For each

tax avoidance measure, we require a constant sample with non-missing data across the event window [-1,

+5]. Industry adjusted tax avoidance measures are adjusted by the average levels of the firms in the same 2-

digit SIC industry in the same year. *, **, and *** indicate statistical significance at the 10%, 5%, and 1%

levels (one-sided), respectively. The Appendix has the variable definitions.

Panel A: Effective Tax Rate Measures

Current ETR Cash ETR

Level Adj. Level Level Adj. Level

Year -1 0.443 0.040** 0.464 0.034* Year 0 0.389 -0.015 0.456 0.029*

Year +1 0.382 -0.016 0.408 -0.016

Year +2 0.366 -0.033* 0.382 -0.037**

Year +3 0.363 -0.036** 0.388 -0.025

Year +4 0.383 -0.014 0.405 -0.004

Year +5 0.356 -0.038** 0.423 0.015

(Year +4) – (Year -1) -0.061 -0.054 -0.060 -0.038

(Year +5) – (Year -1) -0.087*** -0.078*** -0.041* -0.019

No. of Observations 235 235 283 283

Panel B: Book-Tax Difference Measures

MP_BTD DD_BTD

Level Adj. Level Level Adj. Level

Year -1 -0.228 -0.021 0.017 0.011

Year 0 -0.111 0.087*** 0.043 0.029***

Year +1 -0.139 0.062*** 0.040 0.028**

Year +2 -0.088 0.129*** 0.055 0.048**

Year +3 -0.167 0.057 0.054 0.042***

Year +4 -0.103 0.097*** 0.066 0.045***

Year +5 -0.159 0.033 0.066 0.038***

(Year +4) – (Year -1) 0.125*** 0.118** 0.049*** 0.033**

(Year +5) – (Year -1) 0.069 0.053 0.048*** 0.026**

No. of Observations 362 362 335 335

50

Table VII

Impact of Hedge Fund Influence on the Association between

Tax Avoidance and Firm Value

This table presents the results on the impact of hedge fund activists on the association between changes in

target firms‟ tax avoidance and changes in their firm values around hedge fund activist events. The sample

includes firm-years of target firms in the event window [+1, +5] with required data, where event year 0 is the

year of the intervention announcement. Firm-years are classified as without hedge fund influence, if hedge

funds have exited from the firm (i.e., fund ownership falling below 5%). The same set of control variables as in

Table V are included, but coefficients are not reported for conciseness. Changes in Tobin‟s Q, tax avoidance

measures, and control variables are computed relative to the levels in year -1. Also included in the regressions

are year and industry fixed effects dummies. t-statistics reported in parentheses are based on robust standard

errors. *, **, and *** indicate statistical significance at the 10%, 5%, and 1% levels. The Appendix has the

variable definitions.

Panel A: Firm-years under hedge fund influence

Dependent Variable: Tobin‟s Q

Current ETR -0.156***

(-2.99)

Cash ETR -0.184***

(-4.34)

MP_BTD 0.339*

(1.91)

DD_BTD 0.476**

(2.29)

Control Variables Yes Yes Yes Yes

No. of Observations 1,602 1,821 2,016 1,988

Adj. R2 0.477 0.501 0.336 0.327

Panel B: Firm-years without hedge fund influence

Dependent Variable: Tobin‟s Q

Current ETR -0.047

(-0.46)

Cash ETR -0.174**

(-2.41)

MP_BTD -0.023

(-0.06)

DD_BTD 0.505

(0.94)

Control Variables Yes Yes Yes Yes

No. of Observations 660 702 784 772

Adj. R2 0.409 0.466 0.346 0.311