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The Sarbanes Oxley Act of 2002: Implications for Compensation Contracts and Managerial Risk-

Taking

Daniel A. Cohen Stern School of Business, New York University

New York, NY 10012

Aiyesha Dey The University of Chicago Booth School of Business

Chicago, IL 60637

Thomas Z. Lys Kellogg School of Management, Northwestern University

Evanston, IL 60208

September 9, 2009

Abstract

We document that the period following the passage of the Sarbanes Oxley Act of 2002 (SOX) is associated with a significant reduction in compensation-based incentives to take risk, which is related to a decline in risky investments. Moreover, consistent with the rules in SOX directly affecting CEOs’ incentives to take risk, we document that the decline in risky investments exceeds the amount that would be expected from changes in compensation packages alone. Finally, we document that these effects are robust to controlling for the market decline in 2000/2001 as well as the passage of SFAS 123R.

Keywords: Sarbanes Oxley Act; corporate governance; incentive compensation; risk-taking.

We thank Ross Watts (the editor) and an anonymous referee for very helpful comments and suggestions. We are also grateful to Bill Beaver, Phil Berger, Ilia Dichev, Ian Gow, Paul Griffin, April Klein, Mozaffar Khan, Charles Lee, Christian Leuz, Abbie Smith, Paul Zarowin, Jerrold Zimmerman, participants at the 2005 AAA Annual meeting, the 2009 Stanford Summer Camp, and seminar participants at MIT and at the University of Chicago for very useful comments. All remaining errors are our own.

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1. Introduction

In response to the recent corporate scandals, the U.S. Congress enacted the Sarbanes Oxley Act in

2002 (henceforth, SOX) aimed at regulating the governance of firms. While the debate on the overall

implications of SOX is not yet settled, several academics have pointed out that there are likely

to be significant indirect costs associated with SOX, which are likely to exceed the direct

compliance costs (Ribstein [2005]; Bryan and Lillian [2005]). Some of these indirect

opportunity costs result from the Act’s impact on firms’ and mangers’ incentives, and the

resulting changes in compensation plans, operating activities and corporate investment

strategies. In this paper we examine whether and how firms changed incentive compensation of their

CEOs, and the expected consequences such changes in compensation contracts for corporate risk-taking

behavior in the period following the passage of SOX (the post-SOX period).

The financial press has provided some evidence consistent with indirect consequences of SOX. For

instance, executives complain that complying with the SOX requirements has made them divert their

attention from conducting regular business (Solomon and Bryan-Low [2004]).1

1 Solomon, D. and C. Bryan-Low, “Companies Complain about Cost of Corporate-Governance Rules” Wall Street Journal, February 10, 2004.

Moreover, the

academic literature documents firms’ reactions to SOX which are consistent with SOX having imposed

costs on firms, such as firms exiting the U.S. capital markets by either deregistering or going dark after

SOX, and of an increase in voluntary delistings of foreign firms traded as ADRs from U.S. exchanges

(Engel, Hayes and Wang [2007]; Leuz, Triantis and Wang [2008]; Hostak, Karaoglu, Lys and Yang

[2009]). In fact, in a comprehensive study of market reactions to events related to the passage of SOX,

Zhang [2007] finds evidence suggesting that the costs implied by the reduction in market capitalization

around the main SOX events implied by her estimates are not only very large but also far exceed any

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reasonable direct compliance costs of SOX.2

We begin by examining changes in managerial incentive compensation in the period after SOX.

The following reasons motivate our examination of these changes in the post-SOX period. First, several

studies have documented a relation between various aspects of corporate governance, particularly board

structures, and executive compensation [e.g., Yermack [1996]; Core, Holthausen and Larcker [1999];

Vafeas [2003]). These studies document that after controlling for the economic determinants of

executive compensation, various aspects of board structures can explain cross-sectional differences in

executive compensation practices. Dicks [2009] theoretically models the relation between incentive

compensation and governance and argues that as firms are forced to raise the level of governance, they

will lower incentive pay. SOX and the contemporary changes in the rules of the major stock exchanges

resulted in firms having a majority independent board and fully independent compensation, nominating

and audit committees. Further, in addition to the increased monitoring by boards, the period following

SOX is also likely to have witnessed increased vigilance by investors, regulators, auditors and other

market participants. The arguments in the above studies indicate that these governance changes after

SOX are likely to be associated with changes in incentive-based compensation.

Our evidence on the changes in compensation and

corporate risk-taking following SOX is consistent with such indirect costs and also consistent with the

market reactions documented in Zhang [2007].

Second, the legal and political exposure for firms has increased after SOX, which is likely to result

in firms favoring lower risk projects over higher risk projects. This will induce boards to reduce

incentives of their executives to invest in risky projects. Further, as Ribstein [2005] points out,

increased litigation risk may also encourage boards to reduce the level of risk taken by their

corporations and change the reward structure to one that induces CEOs to take less risk.

2 Zhang [2007] examines abnormal returns of U.S. stock markets around key SOX legislative events and finds results indicating that SOX imposes statistically significant net costs on firms. For instance, she documents that the cumulative value-weighted (equal-weighted) raw return of the U.S. market amounts to -15.35% (-12.53%) around the key SOX events. Using various other specifications her results suggest that SOX imposed significant net costs on complying firms (both U.S. firms and U.S. listed foreign firms).

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Finally, in addition to firms’ preferred levels of risky investments in the post-SOX period, rational

boards are likely to anticipate the direct effect of SOX on executives’ risk-taking incentives.

Specifically, the increased personal costs and added liabilities such as the return of incentive based

compensation following accounting restatements (Section 304) are likely to induce corporate executives

to reduce their risk exposures. Any modifications in executives’ incentive compensation plans

introduced by boards will take into account this chilling effect of SOX on executives’ risk-taking

propensities.

We examine the changes in executive incentive-based compensation in the period after SOX, and

find that there were significant shifts in executive compensation to packages that have less incentive-

based compensation.

Our evidence on the post-SOX changes in incentive compensation complements Carter, Lynch and

Zechman [2007], who document that while bonus as a proportion of total compensation of CEOs and

CFOs remained stable over their sample period of 1996 through 2005, bonuses as percentages of salary

and cash compensation both steadily increased in the period after 2001. They conclude that firms placed

significantly more weight on earnings changes in the bonus contract in the post- than in the pre-SOX

period. In fact, our results on the decline in stock and option compensation in the post-SOX period

statistically validate the descriptive trend in option-based compensation after 2001 documented in

Heron, Li and Perry [2007].3

Prior research on trends in executive compensation has generally documented an increase in stock

and option compensation over the last decade, and there is evidence that suggests that the higher levels

of CEO compensation in the U.S. (as compared to the U.K.) are related to the higher risk premiums

(Core, Guay and Larcker [2003]; Conyon, Core and Guay [2006]). Our evidence also contributes to this

3 Heron, Li and Perry [2007] suggest that SFAS 123R is likely to be related to the decline in option-based compensation. However, both our analysis and evidence suggests that these changes were not the consequence of SFAS 123R.

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literature by documenting how the period after SOX is associated with changes in stock- and option-

based compensation.

This trend in incentive compensation following the passage of SOX raises the question of how

these changes affected managerial behavior, and as a result, firm value. Our next objective is to address

this question by analyzing the contemporaneous association between changes in compensation and the

changes in managerial risk-taking in the period following SOX. We term this compensation-induced

change in risk-taking in the post-SOX period as the compensation linkage.

However, note that regardless of any compensation changes, CEOs may reduce investments in risky

projects due to increased personal costs in the period after SOX. Ribstein [2005] argues that SOX

exposes managers and directors to greater litigation risks, and CEOs are likely to take less risky actions,

thus changing their business strategies and potentially reducing firm value. Several SOX mandates

impose specific liabilities on CEOs and on firms. For instance, CEOs face higher risk from both

misreporting of financial information in the form of increased criminal and civil penalties and broader

financial reporting responsibilities, including the certification of financial statements and developing an

internal control system for financial reporting. One likely consequence of these mandates is to reduce

the incentives to invest in risky projects, given the increased penalties resulting from unfavorable

outcomes. As a consequence, CEOs are likely to reduce investments in profitable but risky projects,

leading to a reduction in firm values. We term this effect as the direct linkage.4

We document that our sample firms significantly reduced investments in risky projects in the period

following SOX. While the direct and the compensation linkages are not mutually exclusive, our

evidence suggests that the effect on U.S. firms is through both the compensation linkage and the direct

linkage. While we find a decline in incentive-based compensation, we also find that CEOs’ responses to

risk inducing incentives declined significantly in the post-SOX period. Therefore, the reductions in

investments are not only the consequence of changes in incentive contracts but also the consequence of

4 As discussed earlier, rational boards are likely to anticipate this direct linkage effect while revising executives’ incentive-based compensation contracts.

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increased personal costs on CEOs in the period after SOX. Furthermore, we find evidence indicating

that these changes in investments were, indeed, associated with reduced operating performance of our

sample firms and that these changes are correlated with firm specific stock price changes at the SOX

events.

Our evidence on reduced managerial risk-taking complements a concurrent paper by Bargeron,

Lehn and Zutter [2009] who also document a decline in corporate risk-taking activities after SOX.

Specifically, they also find that companies reduced expenditures in research and development (R&D)

after SOX, and increased holding of cash and cash equivalents (which they characterize as evidence of

non-operating, low risk investments). They also document a decline in the standard deviation of stock

returns in the period after SOX. Bargeron, Lehn and Zutter [2009] further find that the above changes

are more pronounced for larger firms, in firms with high R&D expenses prior to SOX and in firms with

lesser independent directors prior to SOX. Our analysis extends their research and differs from their

analysis by documenting how CEOs’ compensation and incentive structures changed in the post-SOX

period and to what extent such changes in incentive structure, along with the direct personal costs, are

linked to their risk-taking propensities. In combination, our analysis and that of Bargeron, Lehn and

Zutter [2009] provide compelling evidence of the changes in corporate risk-taking in the post-SOX

period, and more importantly, provide evidence of the different channels that are likely to explain this

outcome.

The economic implications of governance reforms form an important research topic, and there has

been considerable academic interest in analyzing the consequences of SOX (e.g., Li, Pincus and Rego

[2008]; Cohen, Dey and Lys [2008]; Engel, Hayes and Wang [2007]; Leuz, Triantis and Wang [2008],

among others). We contribute to this growing literature by providing evidence on the impact of the

governance changes and increased liabilities in the post-SOX period on boards’ executive compensation

policies. We also document that these changes in compensation contracts, in conjunction with direct

personal costs, are associated with changes in CEOs’ investments in risky projects that are related to

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lower operating performance of the sample firms. These results provide one plausible explanation for

the documented large drop in prices on events related to the passage of SOX.

The remainder of the paper proceeds as follows. Section 2 presents the research questions and

develops the hypotheses. Section 3 discusses the data used in the study and presents the summary

statistics as well as some preliminary univariate tests. Section 4 presents the research design and results

of the multivariate tests, and Section 5 concludes.

2. Research Questions and Hypotheses Development

We examine the associations between the passage of SOX and the simultaneous changes in CEOs’

incentive-based compensation and their risk-taking behaviors, recognizing that changes in

compensation made by boards are likely to be in anticipation of risk-taking incentives of CEOs, and the

risk-taking incentives of CEOs will be affected by these compensation changes. Keeping this feedback

effect in mind, we begin by first discussing our hypotheses on the effect of SOX on boards and how

they are likely to change CEOs incentive compensation plans. We then present our predictions on the

shifts in CEOs’ risk-taking behaviors. A summary of our predictions is presented in the Appendix.

SOX and Boards: Implications for Executive Incentive Compensation

The passage of SOX is likely to affect boards’ decisions regarding CEOs’ incentives plans in the

following ways. SOX is a major regulatory intervention that introduced numerous governance reforms,

including reforms related to the functioning of boards of directors. Several studies have provided

evidence of significant relations between governance features (particularly board structure) and

executive compensation contracts (Yermack [1996]; Hallock [1997]; Bertrand and Mullainathan

[2001]; Core, Holthausen and Larcker [1999]). Core et al. [1999] study the relationships among board

composition, ownership structure, and CEO pay. Their results suggest that firms with weaker

governance structures tend to pay their CEOs more. Specifically, they find that CEO pay rises with the

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number of outsiders appointed during the CEO’s tenure, and about whose appointments the CEO

therefore had a say. They also document that CEO pay rises with variables likely to indicate a lack of

board involvement, such as, board size, the number of directors over age sixty-nine, and the number of

“busy” directors, where busy is defined in terms of the number of additional directorships held by a

director. A recent study by Dicks [2009] presents a model where governance and incentive

compensation are substitutes in reducing agency costs. As a result, when governance regulation is

tightened, firms will lower incentive pay. The governance climate strengthened considerably following

the passage of SOX, including firms having more independent boards, fully independent compensation

committees, and greater monitoring by investors, auditors and regulators. The above arguments suggest

that as a consequence of tighter governance standards, we should observe a decline in incentive

compensation in the post-SOX period.

Next, SOX also increased the legal and regulatory scrutiny for corporations, including increased

litigation costs and disruption of business (for example, when corporations are forced to restate

earnings; see Palmrose and Scholz [2004]; Persons [2006]; Arthaud-Day et al. [2006]) as well as the

associated loss of talented managers. These costs are likely to increase in the investments risk and thus

reduce the benefits of investing in risky projects relative to investing in less risky ones.5

5 The United States Government Accountability Office (GAO) report of July 2006 finds that the cumulative total number of restatements was 919 over a 66-month period that ended June 30, 2002, and 1,390 over the 39 month period that ended September 30, 2005. The GAO report further states that over the period of January 1, 2002, through September 30, 2005, the total number of restating companies represents 16 percent of the average number of listed companies from 2002 to 2005, as compared to almost 8 percent during the 1997-2001 period. This anecdotal evidence indicates a significant increase in restatements in the period after SOX.

As a result,

corporations are likely to shift their investments towards projects with a lower exposure to these new

risks, that is, forgo risky investments that they would have undertaken in the absence of SOX (Ribstein

[2005]). Based on the above, we predict that directors are likely to change compensation contracts so as

to lower executives’ incentives to invest in projects that have a higher probability of resulting in these

restatements, write-offs or losses.

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On the other hand, rational boards may take into account the direct effect of SOX on CEOs’

incentives to invest in risky projects (the direct linkage effect discussed in the following section). The

increased personal costs faced by CEOs are likely to induce them to shift towards less risky projects. If

boards are satisfied with this shift, they will leave incentive levels unchanged. However, if boards want

to counteract this effect and to maintain the level of investment to their new optimal level from the

boards’ (and shareholders’) perspectives, then they can intervene by adjusting the CEO’s compensation

packages to induce more risk taking. In this case we expect boards to offset this effect by increasing the

components of compensation packages that induce risk-taking. Finally, if boards conclude that the

reduction in risk due to CEOs’ increased risk-aversions is insufficient, they will reinforce this effect by

reducing the risk-inducing incentives. As a result of these simultaneously interacting forces, the overall

changes in executive incentive compensation in the post-SOX period is an empirical question. 6

SOX and Executives: Implications for Risky Investments

Our next research objective is to examine changes in corporate risk-taking behavior. There are at

least two channels through which SOX can impact the risk-taking behaviors of CEOs. First, executive

behavior is likely to change in the post-SOX period as a direct outcome of the liabilities imposed on

executives by the mandates in SOX. Specifically, as a direct consequence of SOX, CEOs (and other C-

level executives) have broader financial reporting responsibilities, including certification of financial

statements and attestation of the adequacy of internal control systems. As a result, CEOs face higher

6 Prior studies have documented an increase in overall compensation levels as well as an increase in performance related pay following deregulation in the banking industry and the adoption of state-level anti-takeover laws (Hubbard and Palia [1995]; Bertrand and Mullainathan [1999]). In the context of SOX, two related papers on changes in compensation include Wang [2005] and Carter, Lynch, and Zechman [2007]. Wang [2005] examines changes in the level and structure of CFO compensation and documents a decrease (increase) in the weights on public performance measures for firms with strong (weak) board structures and high (low) proportion of uncontrollable risk after the passage of SOX. As mentioned in the introduction, Carter, Lynch and Zechman [2007] document that firms placed more weight on reported earnings in the design of bonus contracts after the implementation of SOX. Also, see Hermalin and Weisbach [2005] for a theoretical framework for evaluating these reforms in SOX.

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probabilities of incurring personal costs from misreporting of financial information such as criminal and

civil penalties, forfeiture of bonuses, and general career concerns (reductions of reputations including

increased likelihood of being dismissed; see Feroz, Park and Pastena [1991]; Desai, Hogan and

Wilkins [2006]; Karpoff, Lee and Martin [2007]). Because the probability of such adverse

consequences is likely to increase as the risk of investment increases, SOX effectively lowers the

payoffs of investing in risky projects relative to investing in less risky projects. As a result, CEOs are

likely to shift investments towards less risky projects, thus forgoing (the more risky) investments that

they would have undertaken in the absence of SOX. We refer to this linkage as the direct linkage.

Second, any changes in incentive-based compensation made by boards will affect CEOs’ risk-

taking behaviors. We refer to this linkage as the compensation linkage. As discussed above, the

increased legal and regulatory scrutiny for corporations in the post-SOX period is likely to induce

boards of directors to shift compensation away from instruments that induce managers to undertake

risky projects (e.g., stock options) to compensations with smaller incentives to invest in risky projects

(restricted stock, bonuses, etc.). This reduction in incentive-based compensation is likely to lead to a

reduction in risky investments as well. However, boards can also increase incentive-based

compensation to counteract the increased risk-aversion of CEOs in the post-SOX period.

The effect of the compensation linkage depends on the direction of the change in incentives induced

by boards. If boards correctly anticipate the direct linkage effect on CEOs’ propensities to invest in

risky projects relative to low-risk projects, and overcome this effect by increasing incentives, then this

predicts an increase in risky investments. However, if boards favor even greater reductions in risky

investments than the direct linkage will result in, then they will reinforce this effect by decreasing

incentives further. This will predict a decrease in risky investments.

Therefore, the direct linkage unambiguously predicts a shift towards less risky investments, while

the prediction for the compensation linkage is not determinable ex ante. However, we still expect a net

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decrease in risk-taking in the post-SOX period for the following reason. Even if the direct linkage

exceeds boards’ desired reductions in risk-taking and they overcome this effect, they will only increase

incentives so as to maintain risky investments to their new preferred optimal, which is likely to be lower

than the pre-SOX levels.7

To investigate the above hypotheses, we analyze changes in compensation packages of CEOs and

changes in risky investments around the passage of SOX. However, there are at least two compelling

confounding events that potentially contribute to a compensation-contract induced reduction in risk-

taking as well as the changes in risky investments and the resulting changes in stock-return volatility in

the period after SOX.

As a result, irrespective of the direction of the compensation linkage, we

hypothesize an overall reduction in risky investments in the post-SOX period.

8 The first event is the passage of SFAS 123R, adopted in December 2004 and

effective for the first quarter of the first fiscal year beginning after June 15, 2005.9

The second confounding factor links changes in investments in risky projects to the market

downturn beginning in the spring of 2000. Specifically, changes in the economic climate after the

“burst” of the internet “bubble” was likely to reduce the benefits of investing in risky projects and

hence, would have changed firms’ investments strategies – absent the passage of SOX. This effect may

Research documents

that companies reduced option-based compensation as a result of the passage of SFAS 123R (Brown

and Lee [2007]). While the economic rationale for why corporations reduced option-based

compensation in response to the mandated expensing of executive compensation options is not

immediately clear, such a shift nevertheless would result in reduced incentives to invest in risky

projects.

7 To illustrate with a simple example, suppose that the pre-SOX level of risky investments for a firm was at a 100, and that the board wants to maintain post-SOX level at 90. Also suppose that the direct linkage effect induces CEOs to shift risky investments towards 70. Ceteris paribus, boards will overcome this effect by increasing incentives so that CEOs increase risky investments to 90 (the board’s preferred level). So even though the compensation linkage is positive, the net effect on risky investments is a reduction by 10 in the post-SOX period. 8 See Dey [2009] for a discussion of some other potential confounding factors that are likely to affect risky investments in the period after SOX. 9 Originally, SFAS 123R was scheduled to be effective for the first fiscal quarter beginning after June 15, 2005. This effective date was modified by the SEC to the first fiscal quarter of the first fiscal year beginning after June 15, 2005. So for calendar-year firms, SFAS 123R applies to the fiscal year 2006.

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well have persisted in the period after SOX as well. In that case, the changes one would observe in the

post-SOX period may be primarily due to firm’s responses to those market events. We conjecture that

firms affected by the market downturn should experience larger changes in their investment strategies

than would firms that did not experience the downturn. We control for these two alternate explanations

in our analyses, so as to better isolate the implications of the passage of SOX on executive incentive

compensation and corporate risk-taking behavior.

3. Data and Summary Statistics

3.1 Data

Our sample comprises industrial companies from the COMPUSTAT annual industrial and research

files and EXECUCOMP and covers the period 1992-2006.10

Merging the COMPUSTAT and

EXECUCOMP databases results in a sample of 1,279 firms with 14,604 firm-year observations. Our

final sample represents only firm-year observations where data for all variables included in the analysis

are available.

3.2 Variable Descriptions and Summary Statistics

Our primary managerial incentive variable of interest is the sensitivity of CEO wealth to stock

volatility, VEGA, measured as the dollar change in the CEO’s wealth for a 1 percent change in the

annualized standard deviation of stock returns. We examine changes in VEGA because it reflects

managers’ incentives to invest in risky projects, as prior research indicates that compensations packages

with higher VEGA are related to implementation of riskier policy choices (Coles, Daniel and Naveen

[2006]).

10 Our sample begins from 1992 as EXECUCOMP does not have data prior to this year. Also, our results are robust to repeating the analysis by excluding utilities, financial and transportation firms, consistent with other empirical studies.

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In addition to VEGA, we also consider the sensitivity of CEO wealth to stock price, DELTA. We

measure DELTA as the dollar change in the CEO’s wealth for a 1 percent change in stock price. A

higher DELTA aligns managers’ incentives with shareholders implying that managers will work harder

to meet organizational goals. However, a higher DELTA also exposes CEOs to more firm risk, and can

induce them to forgo some risky projects (Coles, Daniel and Naveen [2006]). Given that boards are

likely to choose a combination of both DELTA and VEGA components of compensation for

implementing their investment policies, we consider the changes in both these aspects of incentives in

the period after SOX.

Following Guay [1999] and Core and Guay [2002], we rely on the Black-Scholes [1973] option

valuation model as modified by Merton [1973] to compute VEGA and DELTA. We also follow prior

studies in our measure of VEGA of the option portfolio to measure the total VEGA of the stock and

option portfolio (Knopf et al. [2002]; Rajgopal and Shevlin [2002]; Coles, Daniel and Naveen [2006]).

We use two measures of investing in risky projects. The first measure is an “input” measure. Total

risky investments made by firms (INVEST) are computed as the sum of research and development

expenditures, acquisitions, and net capital expenditures (capital expenditures less sale of property, plant,

and equipment) divided by average total assets. All of the individual investment variables are industry-

adjusted by subtracting the industry median value. These measures are consistent with the measures of

risky investments employed in prior studies (e.g., Kothari, Laguerre and Leone [2002]; Coles, Daniel

and Naveen [2006]).11

The second indicator, stock return volatility (STD_RET), measures the consequences of changing

investing strategies. We use this alternative measure because it aggregates the consequences of changes

of several risky actions such as mergers, R&D investments and capital expenditures (Hanlon, Rajgopal

and Shevlin [2004]). Therefore, this measure is likely to capture any effect of changes in risky

investments that we may miss with the variable INVEST.

11 We set research and development equal to zero when it is missing in COMPUSTAT.

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Table 1 presents summary statistics of our main variables as well as some firm characteristics over

the sample period. For a more detailed review, we also present these statistics for the individual

components of the compensation and investment measures. Specifically, with respect to CEO

compensation, we include summary statistics for total compensation (TOTAL), salary (SALARY), bonus

(BONUS), and options value (OPTION). We also report summary statistics for the two primary

components of the INVEST variable, namely research and development expenses (RD), and capital

expenditures (CAPEX).

The primary observations on the key variables are similar to the values reported in related studies.

The sample is dominated by large firms, primarily due to the requirement that firm observations be

present in the EXECUCOMP database. The results in Table 1 indicate that options and salary are the

two dominant components of compensation for the sample firms and that on average, incentive-based

compensation (options and bonuses) comprised a significant portion (over 50%) of the total

compensation for CEOs of the sample firms over the 1992 through 2006 period. In the next section we

present the trends in the above variables over time.

3.3 Trends in Compensation and Risky Investments

Figures 1A through 1D, Figure 2 and Figure 3 depict the trend in the compensation, incentive and

investment variables over the entire 1992-2006 sample period. As is apparent from these figures, the

variables of interest exhibit significant time-series non-stationarities, rendering a traditional summary

statistics uninformative. These time-series non-stationarities are likely to have resulted from the events

in the last decade (such as rapid increases in the portion of options-based compensation in the 1990s,

the bursting of the stock market bubble in 2000/ 2001 and the corporate accounting scandals in

2000/2001).

We investigate these over-time trends more formally by regressing each variable on a time trend

and both SOX intercept and time-trend dummy variables (taking the value of one in the post-SOX

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period, i.e., 2002 onwards, and zero otherwise). In addition to the compensation and investment

variables, we also examine whether there was a change in operating performance (proxied by the return

on assets, ROA), possibly due to the concurrent changes in investments. Table 2 reports the results of

the above regression.

The results indicate that total compensation of $688,181 increased by $269,832 per year and that

increase is significant at conventional levels. However, while we observe a “jump” in compensation of

$71,671 in 2002 and an increase in the time trend of compensation of $12,251 per year after 2002,

neither of these two effects are significant at conventional levels.

Consistent with the compensation literature (see Core, Guay and Larcker [2003] for a survey), we

observe a significant over-time increase in options as a fraction of total compensation of 1.2 percentage

points per year. However, the passage of SOX reduced the fraction of option compensation by 6.4

percentage points and reduced the trend by 1.9 percentage points per year – making the trend after SOX

actually negative – coupled with significant over-time decreases in both salary and bonus

compensation.

Conversely, the percentages of salary and bonus declined from the 1996 levels of 47.6 percent and

19.4 percent by 1.8 and 0.1 percentage points per year, respectively. However, the period of the

passage of SOX reversed that trend, with the percentages of salary and bonus increasing by 4.7 and 4.1

percentage points in 2002 and by 4.2 and 0.5 percentage points per year thereafter. Consistent with the

changes in the compensation mix, we observe a similar pattern in DELTA and VEGA. However, the

decrease in the time-series trend (as opposed to the level) in those two variables after SOX is not

statistically significant at conventional levels.

The investment variables INVEST and its component RD and CAPEX are plotted in Figure 2. The

regression analysis indicates an insignificant time trend in INVEST and R&D prior to SOX and a

significant negative time trend of -2.3 percentage points in CAPEX prior to SOX. However, all three

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investment proxies decreased significantly in 2002 but the subsequent time-trend, while negative, is not

statistically significant at conventional levels.

The time trend of stock return volatility (STD_RET) is depicted in Figure 3. The regression

analysis indicates an increase in STD_RET by 2.2 percentage points per year until the passage of SOX.

However, this time trend was reversed in 2002, with a decline in STD_RET of 26.9 percentage points

and subsequent drops of roughly 2 percentage points per year (0.022 – 0.041). Finally, an analysis of

operating performance, ROA, showed no time trend either before or after the passage of SOX, but

revealed a significant decline by 1.3 percentage points in 2002.

In summary, our preliminary analysis indicates that in the period after the passage of SOX there

was a shift in the compensation structure towards more fixed salary, more bonus compensation and less

option-based compensation (with simultaneous reductions in DELTA and VEGA). The evidence is

consistent with boards altering CEOs’ compensations to reduce their risk-taking incentives. These

univariate results also indicate that there has been a significant decline in risky investments by firms in

the post-SOX period as compared to the period prior to SOX. The results on the stock return volatility

are consistent with this behavior.

3.4 Changes in Risky Investments and Operating Performance in the Post-SOX Period

Investors are likely to anticipate that firms’ will respond to SOX by reducing risky investments,

and the expected opportunity costs of these changes are likely to be increasing in the reduction in risky

investments in response to SOX.12

12 Note that this is true assuming that on average, the level of investments prior to SOX was optimal.

In line with this conjecture, we expect firms that had the most

reduction in risky investments after the passage of SOX to have the most negative market reactions in

response to SOX. Moreover, those reductions in investments are likely to translate to lower operating

performances subsequent to SOX.

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We perform a preliminary examination of whether the association between changes in risky

investments and changes in operating performance from the pre-SOX to the post-SOX period are

related to the market reactions to SOX. We begin by identifying a set of key legislative events related

to the passage of SOX as identified in Zhang [2007]. These events are described in Table 3, Panel A,

and are events which witnessed significant negative market reactions. We cumulate the abnormal

returns for every firm in our sample during these event windows and use these cumulative abnormal

returns to form deciles based on the extent of the negative reaction. Decile (1) corresponds to the

portfolio of firms that had the lowest (most negative) abnormal returns and decile (10) corresponds to

the portfolio of firms that had the highest (least negative) abnormal returns.

We investigate the association between market reactions to SOX related events and changes in

risky investments (∆INVEST), changes in stock return volatility (∆STD_RET) and changes in average

operating performance (∆AVG_ROA) by regressing those variables on the return deciles at the SOX

event dates. We expect the firms with the largest declines in risky investments to be the ones to witness

the most negative reactions during the events related to the passage of SOX and vice versa. The

regression results are reported in Panel B of Table 3. As expected, the results indicate a positive

correlation between the stock price responses at the announcement dates of SOX and subsequent

changes in investments (p = 2.14%), subsequent changes in stock return volatility (p = 10.6%), and

subsequent changes in operating performance (p < 1%).

In further analyses, in Panel C of Table 3, we rank the firms by abnormal returns at the SOX event

dates into three groups and compare the means of those three variables of the 33 percent of the firms

having the most negative responses to those of the 33 percent of the firms with the least negative

abnormal returns at the SOX event dates.13

13 We perform this additional test based on the results in Lys and Sabino [1992] which show that forming roughly three groups, results in the most powerful tests of these grouping-based tests.

As before, we expect the difference in the values of

∆INVEST and ∆STD_RET between group (3) (least negative abnormal returns) and group (1) (most

negative abnormal returns) to be significantly positive. Such declines in investments are likely to be

17

related to declines in operating performance. Therefore, we expect the difference in the values of

∆AVG_ROA between group (3) and group (1) to be significantly positive.

Consistent with our conjectures, the results reveal that the difference between ∆INVEST and

∆STD_RET for firms in group (3) and group (1) is positive and statistically significant. While the

changes in investments are not monotonically related to the market reactions to SOX, the results

indicate that risky investments and volatility of returns were significantly higher prior to SOX for firms

that had the most negative reactions to events related to the passage of SOX. One interpretation is that

the market correctly anticipated that these firms are likely to reduce such investments in response to

events related to SOX, thus identifying one of the potential costs of the passage of SOX.

This inference is further supported by the declines in average operating performance in the period

after SOX. We find that the difference between ∆AVG_ROA for firms in group (3) and firms in group

(1) is positive and statistically significant. In fact the decline in average return on assets is

monotonically related to the drop in returns on the SOX events, indicating that the changes in

investments were, indeed, associated with reduced operating performance of our sample firms.

These tests provide support to our conjectures regarding the effect of the passage of SOX on risky

investments and form a compelling motivation for more formal analyses on this relation. In the next

section, we conduct some multiple regression tests of the changes in compensation and investments

after the passage of SOX. In doing so, we control for the effects of alternative events, namely, the

bursting of the internet bubble and the passage of SFAS 123R, to isolate the impact of the passage of

SOX on firms’ compensation and investment policies.

4. Multiple Regression Analyses : Compensation and Risky Investments in the Post-SOX Period

4.1 Research Design

In this section we examine the changes in managerial incentives and risky investments in the post-

SOX period. As stated earlier, the overall effect on incentive compensation in the period following

18

SOX is unclear, and any changes are likely to be related to the direct linkage and / or the compensation

linkage. To examine the changes in CEOs’ incentive compensation, we estimate the following

regression:

, 0 1 2 3 4 5

6 7 8 9 10

11 12 13 14

_ _ _ _ _ _

_ 00 _ 01_

123

j t jt jt jt jt jt

jt jt jt jt jt

jt

COMP VAR INVEST STD RET O COMP VAR CASH COMP LOG SALESTENURE M B RETURN AUG AUG RET LEVERAGETIME SOX SFAS R INVEST SO

α α α α α α

α α α α α

α α α α

= + × + × + × + × + ×

+ × + × + × + × + ×

+ × + × + × + × × 15

16 17

_

123 _ 123jt jt jt

X STD RET SOXINVEST SFAS R STD RET SFAS R

α

α α ε

+ × ×

+ × × + × × +

... (1)

In equation (1) we investigate two aspects of managerial incentives, represented by the dependent

variable COMP_VAR, which is either VEGA or DELTA. If boards were to change managerial incentives

to affect their risk-taking preferences, then such changes are likely to be directly reflected in VEGA

(Coles, Daniel and Naveen [2006]). While we focus on VEGA as our main incentive variable, we also

consider changes in DELTA because while higher DELTA aligns managers’ incentives with

shareholders, it also exposes managers to more firm-specific risk. Therefore, changes in DELTA are

likely to be related to changes in CEOs’ investments in risky projects as well (Coles, Daniel and

Naveen [2006]). The changes in incentive compensation in the post-SOX period are likely to be

reflected in the SOX dummy variable. For each of the dependent incentive variables, we include the

other incentive variable as a control (represented by O_COMP_VAR in equation (1)) because changes

in VEGA and DELTA will be directly related to each other.

We next examine the changes in risky investments in the period following SOX. We measure risky

investments made by firms, RISKY_INVESTMENTS, by either the variable INVEST or the variable

STD_RET. We estimate the following regression:

0 1 2 3 4 5

6 7 8 9

13 1410 11 12

_ _ _

_ _ 00 _ 01_

123

jt jt jt jt jt jt

jt jt jt jt

jt jt

RISKY INVESTMENTS VEGA DELTA TENURE CASH COMP LOG SALESM B SALES GROWTH RETURN AUG AUG RET

SFAS R VEGLEVERAGE TIME SOX

α α α α α α

α α α α

α αα α α

= + × + × + × + × + ×

+ × + × + × + ×

× + ×+ × + × + × +

15 16 17123 123jt

jt jt jt jt

A SOX

DELTA SOX VEGA SFAS R DELTA SFAS Rα α α ε

×

+ × × + × × + × × + ... (2)

19

In both the above models, we predict a positive association between the investment variables

(INVEST and STD_RET) and VEGA, as higher VEGA is directly linked to managers’ incentives to

invest in risky projects. However, the relation between the investment variables and DELTA is not clear.

Higher DELTA aligns managers’ incentives with shareholders, and thus managers may invest in more

risky investments if that maximizes shareholder value. However, higher DELTA also exposes managers

to more firm risk, and can induce managers to forgo some risky projects (Coles, Daniel and Naveen

[2006]).

The other control variables we use in equations (1) and (2) are consistent with those used in prior

research (Guay [1999]; Coles, Daniel and Naveen [2006]; Bens, Nagar and Wong [2003]). In equation

(1) we use logarithm of sales (LOG_SALES) as a proxy for firm size. Larger firms require more talented

managers who are more highly compensated (Smith and Watts [1992]). Under the typical assumption

that managers’ utility functions exhibit declining absolute risk aversion, CEOs of larger firms are likely

to have higher equity incentives (Core and Guay [1999]; Himmelberg et al. [1999]). Thus we expect

firm size to be positively related to both our incentive variables. We include the market-to-book ratio

(M_B) to control for the presence of investment opportunities on incentive compensation, and expect

positive association between both VEGA and DELTA and M_B. The variable RETURN is the

cumulative 12 months returns for year t for firm j. We expect a positive relation between incentives and

RETURN because executives in better performing firms are likely to be awarded greater incentive

compensations.

As in prior studies we include LEVERAGE to control for its effect on VEGA and DELTA. We use

book leverage as in Coles, Daniel and Naveen [2006], defined as the total debt of the firm divided by

total assets.14

14 Welch [2004] argues that market leverage may change passively simply due to stock price performance. Therefore, this may not reflect boards’ compensation policies based on choice of leverage. On the other hand, as Coles, Daniel and Naveen [2006] point out, market leverage may be directly related to CEOs’incentives through its effect on stock price volatility. Therefore, we repeat our tests using market leverage and the results remain materially unchanged.

Boards of firms with high leverage are likely to structure managerial compensation to

20

have low vegas, so that managers choose low risk projects and shareholders bear lower costs of

financial distress (John and John [1993]). Therefore, we expect a negative relation between VEGA and

LEVERAGE. Further, if delta and leverage are substitute incentive alignment mechanisms, then we are

likely to observe a negative relation between DELTA and LEVERAGE as well.

Consistent with the existing literature, we also include the cash compensation of the CEO,

CASH_COMP (sum of salary and bonus) and the number of months the CEO has been in office,

TENURE to control for the risk-aversion of the CEO.15 We include TIME which is defined as the

calendar year minus 1992, and the indicator variable SOX which takes a value of 1 if the observation is

from year 2002 through 2005.16

In our risky investments equation (equation (2)), where the dependent variable is either INVEST or

STD_RET, we include control variables that are likely to be associated with investments as evidenced in

the prior literature. We include LOG_SALES (defined earlier) to proxy for firm size and expect a

negative relation between the investment variables and LOG_SALES. We also include

SALES_GROWTH defined as the percentage change in sales from the prior year to measure the growth

rate in sales of the firm, and expect a positive coefficient for this variable (Coles, Daniel and Naveen

[2006]).

These variables capture whether CEO DELTA and VEGA have been

changing over time and whether there was a significant change in these aspects of incentives in the

post-SOX period.

Guay [1999] shows that firms with greater growth opportunities provide more risk-taking

incentives and that firm risk is greater when managers have more risk-taking incentives. Thus we

include the market-to-book ratio, M_B, as the measure of growth opportunities and expect a positive

coefficient on this variable. Bhagat and Welch [1995], in a study of R&D expenditures, show that in

15 We also repeat the equation with VEGA as the dependant variable by excluding TENURE as in Coles, Daniel and Naveen [2006], and the corresponding results are consistent with those reported in the paper. 16 To provide a more conservative test of the SOX-based hypotheses, we only define the SOX dummy through 2005 to avoid interaction with the passage of SFAS 123R. We also repeat our analyses by using individual year dummies for the entire sample period. See section 4.3 for a detailed discussion of these robustness tests.

21

addition to market-to-book ratio, a firm’s stock returns can affect the investment decision. We also

include the cumulative 12 months returns as a control variable and expect a positive relation between

returns and risky investments. Apart from being a measure of performance, high stock returns are also

likely to signal future opportunities and lower current cost of capital, and managers in such firms are

likely to increase investments in risky projects.

We include LEVERAGE to control for the association between financing policy and investments

and expect a positive relation (Coles, Daniel and Naveen [2006]). As in equation (1), we include

CASH_COMP and TENURE to control for the level of risk aversion of CEOs. Berger et al. [1997]

argue that CEOs with longer tenures and higher cash compensation are more likely to be entrenched

and will seek to avoid risk. CEOs with higher total cash compensation are also likely to be better

diversified and therefore less risk averse (Guay [1999]). As before, we include the variable

TIME which captures the trend over time in the corresponding dependent variables. The indicator

variable SOX captures the change in the risky investments by CEOs and the changes in compensation

structures after the passage of SOX.17

As mentioned in Section 2, there are at least two alternative explanations for the changes in

managerial incentives and risky investments in the period after SOX: the passage of SFAS 123R and

the burst of the internet bubble. To distinguish from the effects of these confounding factors, we include

two additional controls in equations (1) and (2) based on the following methodologies.

17 We also repeated the above tests by including cash flows from operations, CASH_OPERS, in the two equations to proxy for the real economic environment and performance. We include this variable to control for the effect of economic activity on firms’ research and development expenses and capital expenditures, and on the incentives offered to them. Cash flow from operations is positive and significant in both cases, but the results for the other variables are materially unchanged. The results remain unchanged on repeating the tests using the annual percentage change in real GDP instead of cash flow from operations to control for overall changes in macroeconomic conditions.

22

SFAS 123R was adopted in December 2004 and effective for the first quarter of the first fiscal year

beginning after June 15, 2005.18

Prior research documents that companies reduced option-based compensation as a result of the

passage of SFAS 123R (Brown and Lee [2007]). However, while SFAS 123R reduced earnings for our

sample firms, it had no cash-flow implications. Therefore, we are skeptical that firms will change

incentive compensation that has potentially large implications for corporate investments to avoid having

to expense the associated earnings reduction.

While SFAS 123R was not effective in the periods immediately after

SOX, (i.e., 2003, 2004 and 2005) there were several early adopters during this period that could have

changed their compensation structures in response to the adoption. We control for this possibility by

eliminating all early adopters from our sample. We consult the Bear Stearns Equity Research Report

[2003] and the KPMG SFAS 123 Voluntary Adopters Compensation Study [2004] to obtain a

comprehensive list of voluntary adopters. Most of these early adopters have adopted SFAS 123R in

2002 or 2003.

Although SOX was passed in 2002 which is much before the period of mandatory adoption of

SFAS 123R, we include an indicator variable, SFAS123R, which takes the value of 1 if the observation

is from the year 2006 and 0 otherwise.19

Next, we control for effect of the internet bubble and market downturn as follows. We first plot the

returns of the S&P 500 firms (these firms mainly comprise our sample) and observe that the major

This variable will capture any impact of SFAS 123R on

managerial incentives and risky investments and will further separate out the effect of SFAS 123R. If

firms did indeed reduce managerial incentives and CEOs reduced investments in response to SFAS

123R, then we expect a negative coefficient for the indicator SFAS123R and for the interactions of the

incentive and investment variables.

18 Originally, SFAS 123R was scheduled to be effective for the first fiscal quarter beginning after June 15, 2005. This effective date was modified by the SEC to the first fiscal quarter of the first fiscal year beginning after June 15, 2005. So for calendar-year firms, SFAS 123R applies to the fiscal year 2006. 19 Because we defined the SOX dummy to be zero in 2006, SFAS123R captures both the effect of SOX and the effect of firms’ adoption of SFAS 123R. As a result, the dummy variable SOX is a conservative indicator of the SOX effect.

23

downturn for these firms began around August 2000 and continued through August 2002. Since the

major scandals beginning with Enron started around October 2001, we consider the period between

August 2000 and August 2001 as our indication of firms most hit by the downturn following the

internet crash. We then compile the returns for all firms in our sample between August 2000 through

August 2001 and form deciles based on these returns. Decile 1 comprises firms with the most negative

returns, and therefore the firms most affected by the internet crash, and decile 10 comprises firms with

the least negative returns. We include these decile rankings, represented by the variable

AUG00_AUG01_RET, to control for the effect of the market crash. If the primary changes in CEOs’

compensation and incentives and their investments were due to the market downturn, we should not

find a significant coefficient for the indicator variable SOX once we control for this downturn effect. If

firms most hit by the market crash did indeed reduce incentives and investments the most, then we

expect a positive association between AUG00_AUG01_RET and the corresponding dependant

variables.20, 21

The research design discussed in this section ignores the possibility that the incentive and

investment variables are likely to be determined simultaneously. Boards are likely to make changes in

managerial incentives by taking into account CEOs’ responses in terms of investment decisions, and

CEOs’ investment choices will reflect these changes in incentives. Thus, the action choices of CEOs

and their incentive structures are likely to be directly related to each other, and studying these choices in

an ordinary least squares frameworks may lead to biased parameter estimates. To verify that our results

and inferences are robust to this possibility, we repeat our analyses by employing a three-stage least-

squares (3SLS) model as the empirical representation of the relationship between the investment

20 Note that our sample begins from 1992 and the variable AUG00_AUG01_RET represents the return deciles for the period August 2000 through August 2001. Therefore this variable is coded as zero in every period prior to August 2000. 21 As pointed out by the referee, if our existing model for compensation and investments captures the changes in investment opportunities due to the bursting of the bubble, then we will not observe any significant coefficient for this variable.

24

choices of CEOs, VEGA and DELTA. The structural equations for the three-stage least-squares

regressions are discussed below.

The specification of the three-stage least-squares model and the identifying restrictions we use

closely follows that in Coles, Daniel and Naveen [2006] and the references discussed therein. The

jointly determined variables are the investment measure (either INVEST or STD_RET), VEGA, and

DELTA. Specifically, we estimate the following system of equations:

0 1 2 3 4

5 6 7 8

9 10

1411 12 13

_ _

_ _

_ 00 _ 01_

123

jt jt jt jt jt

jt jt jt

jt jt

jt jt

RISKY INVESTMENTS VEGA DELTA TENURE CASH COMPLOG SALES M B CASH RETURNSALES GROWTH AUG AUG RET

SFASLEVERAGE TIME SOX

α α α α α

α α α α

α α

αα α α

= + × + × + × + ×

+ × + × + × + ×

+ × + ×

×+ × + × + × + 15

16 17 18123 123jt

jt jt jt jt

R VEGA SOX

DELTA SOX VEGA SFAS R DELTA SFAS R

α

α α α ε

+ × ×

+ × × + × × + × × +

0 1 2 3 4

5 6 7 8

12 139 10 11

14 15

_ _

_ _ 00 _ 01_

123

_

jt jt jt jt

jt jt jt jt

jtjt jt

jt

VEGA INVEST STD RET DELTA CASH COMPLOG SALES M B RETURN AUG AUG RET

SFAS R INVEST SOXLEVERAGE TIME SOXSTD RET SOX

α α α α α

α α α α

α αα α α

α α

= + × + × + × + ×

+ × + × + × + ×

× + × ×+ × + × + × +

+ × × + 16123 _ 123jt jt jtINVEST SFAS R STD RET SFAS Rα ε× × + × × +

, 0 1 2 3 4 5

6 7 8 9 10

11 12 13 14 15

_ _

_ _ 00 _ 01_

123

j t jt jt jt jt jt

jt jt jt jt jt

jt jt

DELTA INVEST STD RET VEGA TENURE CASH COMPLOG SALES M B CASH RETURN AUG AUG RETLEVERAGE TIME SOX SFAS R INVEST

α α α α α α

α α α α α

α α α α α

= + × + × + × + × + ×

+ × + × + × + × + ×

+ × + × + × + × + × ×

15 16 17_ 123 _ 123jt jt jt jt

SOXSTD RET SOX INVEST SFAS R STD RET SFAS Rα α α ε+ × × + × × + × × +

Our results on the changes in investments, vega, and delta are similar across the above specifications,

and therefore, instead of discussing the results for each specification separately, we provide a

consolidated discussion of the results in the next section.

4.2 Results

Executive Incentive Compensation in the Post-SOX Period

Table 4 presents the results of the ordinary least squares framework, while Table 6, Panels A and B

summarizes the results of the three-stage least-squares framework. The results for VEGA and DELTA

25

are very similar, and because our primary focus is on VEGA, we discuss the results for VEGA and point

out the differences with respect to DELTA if any.

Consistent with the results of the summary statistics, VEGA increased over time and declined

significantly in the post-SOX period. This trend is likely to be largely due to the decline in option-

based compensation (see Table 2). This evidence indicates the post-SOX period is associated with a net

decrease in incentive pay. The trend in DELTA is similar to VEGA. The significant decline in DELTA

after SOX reduces the alignment of the CEOs’ wealth with shareholders’ but also makes compensation

less risky, thus counteracting the effect of a reduction in VEGA on risk-taking.

Consistent with expectations, we obtain a positive coefficient for both proxies for risky

investments, INVEST and STD_RET, in line with the notion that higher VEGA induce higher

investments in risky projects. This result is also true for the DELTA, confirming our inference above

that for this sample increases in DELTA are related to higher investments in risky projects (i.e. that the

incentive alignment dominates the compensation risk effect). Both interaction terms, INVEST×SOX and

STD_RET×SOX, are negative and statistically significant, suggesting that in the post-SOX period for

every unit of VEGA the investments in risky projects significantly declined. This is also evidence in

support of the direct linkage hypothesis, wherein, for a given level of VEGA, CEOs’ incentives to invest

in risky projects have declined after SOX because of increased personal costs. While it is possible that

CEOs reallocated investment dollars to other (maybe less) risky projects that are not captured by our

total investment measure INVEST, this effect should nevertheless be reflected by the volatility measure

STD_RET which captures the effect of all investments. The results for STD_RET strengthen the

conclusion that the incentives to undertake risky investments declined after SOX.

The results for the control variables generally conform to prior studies in the area. For instance, we

obtain a positive and significant coefficient for LOG_SALES suggesting that larger firms offer higher

risk-taking incentives to their CEOs. We obtain a positive and significant coefficient for RETURN,

suggesting that CEOs in better performing firms have higher levels of incentive compensation. While

26

the coefficient for LEVERAGE is not significant for VEGA, it is negative and significant for DELTA. As

in prior studies, the coefficients for M_B and for CASH_COMP are positive and significant. The

coefficient for TENURE is positive and marginally significant. The results also indicate that

compensations structures are determined such that a higher VEGA implies a higher DELTA and vice

versa.

More importantly, we find no evidence supporting the alternative explanations that changes in

incentives are a response to the market downturn beginning in August 2000 or the adoption of SFAS

123R. Specifically, the variable AUG00_AUG01_RET is insignificant, suggesting that boards did not

change managerial incentives in relation to the internet crash (or that this effect is captured by the other

variables in our model). The indicator variable (as well as the related interaction term) SFAS123R is

also insignificant, indicating that firms did not change managerial incentives in response to the passage

of SFAS 123R. Note that we only have one year (year 2006) that coincides with the mandatory

adoption of SFAS 123R and thus our conclusion regarding the effect of 123R on managerial incentives

may be premature. However our interest is whether this affected the results related to the passage of

SOX. The significant results for the SOX dummy (despite of controls for both confounding factors)

provides greater assurance that the observed changes in managerial incentives following SOX were

primarily due to the governance and other changes in the period following SOX. The next section

formally examines changes in risky investments by CEOs in the period after SOX.

Risky Investments in the Post-SOX Period

Table 5 presents the results of the ordinary least squares, while the results of the simultaneous

equations model are presented in Table 6, Panels A and B. The results for the two investment variables

are similar and we discuss only the results for INVEST, but point out the differences in results for

STD_RET whenever applicable.

27

Similar to our preliminary results in Table 2, investments in risky projects increased over time,

while there was a significant decline in risky investments by CEOs in the post-SOX period. This is

consistent with our conjecture that there is likely to be a decline in investments in risky projects after

SOX. This evidence is consistent with the results in Bargeron, Lehn and Zutter [2009] who document a

decline in R&D expenditures and standard deviation of stock returns in the period after SOX. They also

document an increase in cash and cash holdings in the period after SOX which they interpret as

evidence of increase in lower risk investments in the period after SOX.22

Both equity incentive variables VEGA and DELTA are positively associated with INVEST,

consistent with expectations. However, while VEGA is positively associated with STD_RET, DELTA is

negative and significantly associated with STD_RET. This is consistent with the argument that higher

DELTA may induce undiversified CEOs to shy away from risky projects as they are exposed to higher

firm risk, but is inconsistent with the results corresponding to INVEST. It is possible that STD_RET is

capturing the effect of DELTA on some other investments which are not captured by the variable

INVEST.

The coefficients for the interaction terms VEGA×SOX and DELTA×SOX are negative and

significant. These results also support the direct linkage. This suggests that CEOs’ investment decisions

are less sensitive to their incentives in the period after SOX than before SOX. Therefore there are

additional constraints that are related to the reductions in investments post SOX, which are consistent

with the direct costs imposed by SOX on CEOs. In combination with the earlier results, we find that

boards have reduced VEGA and DELTA after SOX, and CEOs have reduced risky investments in the

post-SOX period and these investment decisions are less sensitive to the incentives provided. Together

these results provide support for both the direct linkage and the compensation linkage.

22 One confounding factor in interpreting the evidence on cash holdings as a shift to less risky investments due to SOX stems from the evidence in recent studies which document that cash holdings for U.S. firms more than doubled from 1980 to 2006 as a result of a secular trend rather than a recent buildup of cash holdings of some large firms (Bates, Kahle and Stulz [2007]). Further, Foley, Hartzell, Titman, and Twite [2007] show that one reason for the cash buildup is that U.S. firms had foreign profits that would have been taxed had they been repatriated.

28

The results for the control variables are generally consistent with prior research. As expected,

INVEST is negatively related to LOG_SALES and RETURN, and positively related to the market-to-

book ratio, M_B. The relation between investments and LEVERAGE is positive but not significant at

conventional levels. The coefficient corresponding to CASH_COMP is positive and significant, but

TENURE is negative and significant. These results suggest that CEOs with longer tenure avoid risk, but

those with more cash compensation invest more in risky projects, possibly because they are better

diversified.

As in the case with managerial incentives, we find no evidence supporting the alternative

hypotheses that changes in investments are primarily a response to the market downturn beginning in

August 2000 or the adoption of SFAS 123R. The indicator variable (as well as the related interaction

terms) SFAS123R is insignificant, indicating that CEOs did not change their investment policies in

response to the passage of SFAS 123R. The variable AUG00_AUG01_RET is insignificant for INVEST

but negative and significant for STD_RET. The negative coefficient in the case of STD_RET is contrary

to expectations because one would expect firms that were the most affected by the market crash to

reduce their investments the most. But the negative coefficient suggests that the firms with lower

returns (so the lower deciles) made more investments in risky projects. While we cannot explain this

result, the significant negative coefficient on the indicator variable SOX after controlling for the effect

of the market crash and SFAS 123R further confirms that the decline in investments in the post-SOX

period were not due to these alternative explanations.

Overall, our analysis provides evidence that firms reduced investments in risky projects following

the passage of SOX. While this change was in part due to boards adjusting CEOs incentives to lower

their VEGAs and DELTAs (the compensation linkage), it was also due to the huge personal costs that

executives face in the post-SOX period (the direct linkage). Moreover, our analysis controls for the

29

internet crash in August 2000 and the passage of SFAS 123R and rules out these events as the primary

cause of the documented changes in risky investments.23

4.3 Robustness Tests

In our multiple regression analyses in Tables 4, 5 and 6, we combine the years 2002, 2003, 2004

and 2005 to indicate the post-SOX period and use an indicator variable to represent it. However, using

the individual years along with interactions is likely to give clearer evidence of these compensation and

risky investment changes in the post-SOX period. Therefore, we repeat our analyses by including

individual year dummies for all years in the sample period, and including interactions for the

compensation and risky investment variables in each of the years after SOX.24

The results for the investment variables also reinforce our inferences. Both variables representing

risky investments declined significantly in the years 2002, 2003, 2004 (except that the decline in

STD_RET for 2002 was not significant; and STD_RET was also significantly lower in 2005). Further,

We find that our primary

compensation variable of interest, VEGA, declined significantly for each of the years 2003, 2004, 2005

and 2006, although the change in 2002 is not significant. This is not surprising given that SOX was

passed towards that end of 2002 and any subsequent changes in compensation contracts will only be

observable from the next year onwards. The interactions with the two investment variables (INVEST

and STD_RET) are negative and significant for the years 2003, 2004 and 2005, but the interaction with

2006 is negative but not significant. The results are similar for the variable DELTA, except that the

changes in DELTA in the years 2005 and 2006 are not significant. The above results reinforce the

decline in incentive compensation in the years following SOX and also suggest that SFAS 123R was

not likely to be associated with changes in VEGA or DELTA.

23 While ruling out these two major potential explanations provides a very strong argument for SOX being the cause of these changes in investments and managerial incentives, we do acknowledge the possibility that other concurrent events in the post-SOX period may have contributed to these declines (Dey [2009]). 24 We thank the editor for this suggestion. These results are not reported for the sake of brevity, but are available upon request.

30

the interactions with VEGA are negative and significant in the years 2002 and 2003 and 2004 (2004 was

not significant in the case of INVEST), and interactions with DELTA were significant for the years 2002

(2002 is not significant in the case if STD_RET), 2003 and 2004.

Overall, the above results are consistent with a significant decline in incentive-based compensation

in the years following SOX (particularly 2003 and 2004, after which the changes are likely to have

stabilized). These changes in compensation are also associated with significant declines in risky

investments, particularly in 2003 and 2004. These results give us more confidence in our inferences on

the changes in incentive compensation and risk-taking in the post-SOX period.

5. Conclusion

Our analysis contributes to the ongoing debate on the impact of SOX by providing evidence that the

period after the passage of SOX was associated with changes in incentive-based compensation and

managerial investment strategies. These changes in investment strategies were associated with stock

price changes around the passage of SOX and reduced operating performance in the years following

SOX. Specifically, we document that the passage of SOX was followed by a significant decline in

incentive compensation awarded to CEOs and risky investments by corporations. We also document

that these changes in investments were not only related to shifts in incentive compensation of CEOs,

but were also likely to have resulted from an increase in direct personal costs that SOX imposes on

CEOs. Further, our evidence that the changes in investments are related to lower operating

performances of firms suggests that these changes were costly to investors.

Our evidence on changes in risk-taking in the post-SOX period complements the concurrent

evidence of Bargeron, Lehn and Zutter [2009]. We add to their findings by documenting that the

reduction in risk-taking activities is in part linked to changes in executive compensation contracts after

SOX and also related to increased executives’ personal costs of engaging in risky activities. We also

contribute to the literature on the trend in executive compensation and on the relation between

31

governance regulation and executive compensation. In line with the theoretical arguments in the

literature, we provide statistical evidence that the period after SOX was associated with a decline in

incentive compensation awarded to CEOs. Finally, our results are robust to controlling for the possible

changes in risky investments related to the market downturn in 2000/2001 as well as the passage of

SFAS 123R.

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36

APPENDIX SUMMARY OF THE IMPLICATIONS OF SOX FOR COMPENSATION AND RISK-TAKING

SARBANES OXLEY ACT, 2002

CEOs Boards / Shareholders

Direct Linkage: Increased personal costs of high risk

projects

Compensation Linkage: Changes in incentives introduced

by boards

Increased legal and political

exposure results in boards favoring

lower risk projects

Tighter governance

reduces need for incentive compensation

Boards anticipate increased the risk-

aversion of CEOs (the Direct Linkage effect)

and overcome this effect to set risky

investments to a new optimal level from their perspectives CEOs shift towards

less risky investments

(1) If boards correctly anticipate the effect of the Direct Linkage on risk-taking and increase incentives to overcome this effect, then this predicts an increase in risky investments

(2) If boards favor even lower levels of risk-taking and decrease incentives, then this predicts a decrease in risky investments

Decrease in CEOs’ incentives to invest

in risky projects

Decrease in incentive

compensation

Overall effect on incentive compensation: UNCLEAR

Overall effect on risk-taking: DECREASE

Increase in incentive compensation

37

TABLE 1: SUMMARY STATISTICS (1992 – 2006; N= 14,604)

Variable Mean Median Standard Deviation

Risky investments INVEST 0.16 0.09 0.17 RD 0.06 0.01 0.23 CAPEX 0.09 0.06 0.16 STD_RET 0.42 0.35 0.18

Compensation TOTAL ($000s) 2293.12 1487.13 1272.81 SALARY 0.37 0.30 0.29 BONUS 0.18 0.16 0.43 OPTION 0.36 0.32 0.56 VEGA($000s) 86.42 41.39 124.92 DELTA ($000s) 843.37 329.52 1149.32

Operating Performance ROA 0.047 0.058 0.08

Firm Characteristics SIZE 1873.92 789.85 3901.38 GROWTH 0.14 0.11 0.13 CASH_OPERS 0.13 0.12 0.12 CEO_AGE 58.00 56.00 8.00 TENURE 63.00 34.00 43.00 This table presents the means, medians and standard deviations of the main variables used in the analyses, including variables measuring risky investments, CEO compensation, operating performance as well as some characteristics of the sample firms. INVEST is total investments calculated as the sum of research and development expenditures, acquisitions, and net capital expenditures (capital expenditures less sale of property, plant, and equipment) made by the firm divided by average total assets; RD is the research and development expenditures made by the firm scaled by average total assets; CAPEX is net capital expenditures (capital expenditures less sale of property, plant, and equipment) made by the firm divided by average total assets; STD_RET is measured as the annualized standard deviation of daily stock returns; TOTAL is total compensation, where total compensation is variable TDC1 from EXECUCOMP which includes the salary, bonus, restricted stock, other annual compensation, long term payouts and option grants awarded to CEOs; SALARY is the salary received by the CEO of the firm as a percentage of total compensation; BONUS is the bonus compensation received by the CEO of the firm as a percentage of total compensation; OPTION is the average Black-Scholes value of options received by the CEO of the firm as a percentage of total compensation; VEGA is the dollar change in the CEO’s wealth for a 1% change in standard deviation of returns; DELTA is the dollar change in the CEO’s wealth for a 1% change in the stock price; ROA is the return on assets, defined as income from continuing operations divided by average total assets; SIZE is the market value of the firm at fiscal year end; GROWTH is the growth in sales for the year; CASH_OPERS is the cash flow from operations divided by average total assets; CEO_AGE is the CEO’s age; CEO_TENURE is the number of months the CEO has been in office at the time of the current annual report date.

38

TABLE 2: TREND IN INVESTMENTS, COMPENSATION AND OPERATING PERFORMANCE OVER TIME

(1992 – 2006; N= 14,604)

SOXTimeSOXTimeDep jq ××+×+×+= χγβα

Dependent Variables COEFFICIENT (T-STAT.)

α̂ β̂ γ̂ χ̂

TOTAL 681.284 (8.39)

267.452 (9.29)***

69.351 (0.72)

13.134 (1.38)

SALARY 0.481 (12.31)***

-0.017 (-8.13)***

0.049 (6.53)***

0.038 (0.84)

BONUS 0.187 (10.59)***

-0.002 (-1.86)*

0.037 (5.12)***

0.006 (4.74)***

OPTION 0.249 (8.71)***

0.013 (9.26)***

-0.062 (-7.92)***

-0.017 (-4.12)***

VEGA 86.291 (6.28)***

23.137 (7.12)***

-16.246 (-4.79)***

-4.837 (-1.27)

DELTA 872.21 (5.48)***

102.473 (7.26)***

-95.371 (-4.92)***

-7.267 (-1.14)

INVEST 0.116 (7.39)***

0.002 (1.17)

-0.026 (-3.23)***

-0.003 (-0.84)

RD 0.043 (5.35)***

0.002 (1.03)

-0.008 (-2.92)***

-0.002 (-1.02)

CAPEX 0.083 (6.75)***

-0.006 (-3.93)***

-0.019 (-4.89)***

-0.003 (-0.71)

STD_RET 0.332 (9.24)***

0.028 (8.13)***

-0.258 (-10.37)***

-0.049 (-3.79)***

ROA 0.039 (8.65)***

0.000 (0.78)

-0.014 (-2.89)***

-0.002 (-0.36)

***Significant at the 1% level; ** Significant at the 5% level; *Significant at the 10% level. T-statistics in parentheses are based on robust firm-clustered standard errors (Petersen [2007]). This table presents the trend over time of the investment, compensation and return on assets. The dependent variables are defined as follows. TOTAL is total compensation, where total compensation is variable TDC1 from EXECUCOMP which includes the salary, bonus, restricted stock, other annual compensation, long term payouts and option grants awarded to CEOs; SALARY is the salary received by the CEO of the firm as a percentage of total compensation; BONUS is the bonus compensation received by the CEO of the firm as a percentage of total compensation; OPTION is the average Black-Scholes value of options received by the CEO as a percentage of total compensation; VEGA is the dollar change in the CEO’s wealth for a 1% change in standard deviation of returns; DELTA is the dollar change in the CEO’s wealth for a 1% change in the stock price; INVEST is total investments calculated as the sum of research and development expenditures, acquisitions, and net capital expenditures (capital expenditures less sale of property, plant, and equipment) made by the firm divided by average total assets; RD is the research and development expenditures made by the firm scaled by average total assets; CAPEX is net capital expenditures (capital expenditures less sale of property, plant, and equipment) made by the firm divided by average total assets; STD_RET is measured as the annualized standard deviation of daily stock returns; ROA is the return on assets, defined as income from continuing operations divided by average total assets; Time is defined as the calendar year minus 1992; SOX is a dummy variable taking a value of 1 if the observation is from year 2002 through 2006.

39

FIGURES: TREND IN INVESTMENTS AND COMPENSATION OVER TIME, 1992 - 2006

Figure 1A: Total Compensation Over Time (1992-2006)

0

500

1000

1500

2000

2500

3000

3500

4000

4500

1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

Year

Tota

l Com

p (0

00's

$)

TotalInflation adjusted

Figure 1B: Compensation Over Time as Percentage of Total Pay (1992-2006)

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0.5

1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

YEAR

% o

f Tot

al P

ay

SALARYBONUSOPTION

40

41

Figure 2: Investments Over Time (1992-2006)

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

YEAR

% o

f Tot

al A

sset

s

RDCAPXINVEST

Figure 3: Annualized Standard Deviation of Daily Stock Returns Over Time (1992-2006)

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

Year

STD ANN_STD

42

TABLE 3: MARKET REACTIONS TO SOX AND RISKY INVESTMENTS

Panel A Legislative Events Related to SOX

Event Window Description of Event 2/1/2002 – 2/4/2002 Treasury Secretary called for changes in rules governing corporations 7/8/2002 – 7/12/2002 Senate debated Sarbanes’ bill and President Bush delivered a speech on corporate

reforms. The passage of Sarbanes’ bill is likely. On 7/10/2002 the Senate passed a though amendment to strengthen criminal penalties 97 to 0.

7/18/2002 – 7/23/2002 House Republican leaders reportedly retreated from efforts to dilute the Senate’s tough bill.

7/24/2002 – 7/26/2002 Senate and House agreed on the final rule. Senate and House passed SOX. The above table lists four key legislative events related to the passage and implementation of SOX which were found to have significant negative market reactions in Zhang [2007].

Panel B Changes in Risky Investments and SOX Returns

Decile Analysis

DEP_VAR

∆ INVEST ∆STD_RET ∆AVG_ROA

Intercept -0.041*** (-7.92)

-0.293*** (-11.47)

-0.039*** (-13.64)

Slope 0.003*** (2.97)

0.007* (1.84)

0.002*** (8.93)

Adj. R2 0.463 0.226 0.594 ***Significant at the 1% level; ** Significant at the 5% level; *Significant at the 10% level. This table reports the results of a regression of change in investments and average operating performance on the return deciles formed based on the reactions to key legislative events related to SOX. The variable Decile_RET represents the decile rankings. Decile rankings are such that decile (1) corresponds to the portfolio of firms that had the most negative impact, i.e., the lowest cumulative abnormal returns around the events listed in Table 3, Panel A, and decile (10) corresponds to the portfolio of firms that had the least negative impact around these events. The dependent variables are defined as follows. ∆ INVEST is the change in average total investments calculated as the sum of research and development expenditures, acquisitions, and net capital expenditures (capital expenditures less sale of property, plant, and equipment) made by the firm divided by average total assets, between the Post-Sox period (2002-2006) and the Pre-Sox period (1997-2001); ∆ STD_RET is the change in stock return volatility between the Post-Sox period (2002-2006) and the Pre-Sox period (1997-2001) and is measured as the annualized standard deviation of daily stock returns; ∆AVG_ROA is the change in average return on assets, between the Post-Sox period (2002-2006) and the Pre-Sox period (1997-2001) and is defined as income from continuing operations divided by average total assets.

43

Panel C

Changes in Risky Investments and SOX Returns Three Group Analysis

Group ∆ INVEST ∆STD_RET ∆AVG_ROA

(1) -0.045*** -0.276*** -0.017***

(2) -0.027*** -0.224*** -0.008*

(3) -0.023*** -0.259*** -0.006

(3) –(1) 0.022*** 0.017*** 0.011***

***Significant at the 1% level; ** Significant at the 5% level; *Significant at the 10% level. This table reports the differences in risky investments made before SOX by firms separated into three groups based on the reactions to key legislative events related to SOX. Group (1) corresponds to the portfolio of 33.33% of firms that had the most negative impact, i.e., the lowest cumulative abnormal returns around the events listed in Table 3, Panel A, and group (3) corresponds to the portfolio of 33.33% of firms that had the least negative impact around these events. ∆ INVEST is the change in average total investments calculated as the sum of research and development expenditures, acquisitions, and net capital expenditures (capital expenditures less sale of property, plant, and equipment) made by the firm divided by average total assets, between the Post-Sox period (2002-2006) and the Pre-Sox period (1997-2001); ∆ STD_RET is the change in stock return volatility between the Post-Sox period (2002-2006) and the Pre-Sox period (1997-2001) and is measured as the annualized standard deviation of daily stock returns; ∆AVG_ROA is the change in average return on assets, between the Post-Sox period (2002-2006) and the Pre-Sox period (1997-2001) and is defined as income from continuing operations divided by average total assets.

44

TABLE 4: MANAGERIAL INCENTIVES AFTER SOX (1992 – 2006; N=14,604)

, 0 1 2 3 4 5

6 7 8 9 10

11 12 13 14

_ _ _ _ _ _

_ 00 _ 01_

123

j t jt jt jt jt jt

jt jt jt jt jt

jt

COMP VAR INVEST STD RET O COMP VAR CASH COMP LOG SALESTENURE M B RETURN AUG AUG RET LEVERAGETIME SOX SFAS R INVEST SO

α α α α α α

α α α α α

α α α α

= + × + × + × + × + ×

+ × + × + × + × + ×

+ × + × + × + × × 15

16 17

_

123 _ 123jt jt jt

X STD RET SOXINVEST SFAS R STD RET SFAS R

α

α α ε

+ × ×

+ × × + × × +

PANEL A PANEL B

DEPENDENT VARIABLE =

VEGA COEF. (T-STAT.)

DEPENDENT VARIABLE = DELTA

COEF. (T-STAT.)

INTERCEPT 0.021 (3.62)***

0.054 (4.03)***

INVEST 0.186 (3.31)***

9.324 (3.68)***

STD_RET 0.243 (10.52)***

0.041 (2.98)***

O_COMP_VAR 0.044 (3.82)***

3.248 (4.06)***

CASH_COMP 0.038 (16.02)***

0.025 (9.61)***

LOG_SALES 0.037 (13.51)***

0.318 (18.53)***

TENURE 0.006 (1.74)*

0.039 (4.32)***

M_B 0.007 (6.32)***

0.152 (12.38)***

RETURN 0.408 (4.33)***

0.281 (4.17)***

AUG00_AUG01_RET 0.005 (0.61)

-0.005 (-0.81)

LEVERAGE -0.003 (-0.29)

-0.139 (-3.31)***

TIME 12.383 (5.72)***

81.37 (4.68)***

SOX -7.252 (-3.74)***

-53.14 (-3.64)***

SFAS123R -0.002 (-1.13)

0.002 (1.08)

INVEST × SOX -0.036 (-5.18)***

-5.691 (-4.33)***

STD_RET × SOX -0.048 (-6.26)***

-5.741 (-4.09)***

45

Table 4 Contd.

INVEST × SFAS123R -0.004 (-0.44)

0.002 (0.43)

STD_RET× SFAS123R -0.003 (-0.29)

0.003 (0.68)

R-SQUARE 0.403 0.376 ***Significant at the 1% level; ** Significant at the 5% level; *Significant at the 10% level. T-statistics in parentheses are based on robust firm-clustered standard errors (Petersen, 2009). Industry control fixed effects are included. Table 4 presents OLS regression results corresponding to VEGA and DELTA. COMP_VAR and O_COMP_VAR are either VEGA or DELTA, respectively; VEGA is the dollar change in the CEO’s wealth for a 1% change in standard deviation of returns; DELTA is the dollar change in the CEO’s wealth for a 1% change in the stock price; INVEST is the sum of research and development expenditures, acquisitions, and net capital expenditures (capital expenditures less sale of property, plant, and equipment) divided by average total assets; STD_RET is the annualized standard deviation of daily stock returns; CASH_COMP is the sum of salary plus bonus; LOG_SALES is the logarithm of sales; M_B is the market-to-book ratio; TENURE is the number of months the CEO has been in office; RETURN is the cumulative return for the 12 months ending on the compensation grant date for year t for firm j; AUG00_AUG01_RET is the decile ranking of the cumulative returns during August 2000 and August 2001, where the lowest decile corresponds to the most negative returns; LEVERAGE is the firm’s total debt divided by total assets; TIME is the calendar year minus 1992; SOX is a dummy variable taking a value of 1 for the years 2002 through 2005; SFAS123R is a dummy variable taking the value of 1 for the year 2006.

46

TABLE 5: RISKY INVESTMENTS AFTER SOX (1992 – 2006; N=14,604)

0 1 2 3 4 5

6 7 8 9

13 1410 11 12

_ _ _

_ _ 00 _ 01_

123

jt jt jt jt jt jt

jt jt jt jt

jt jt

RISKY INVESTMENTS VEGA DELTA TENURE CASH COMP LOG SALESM B SALES GROWTH RETURN AUG AUG RET

SFAS R VEGLEVERAGE TIME SOX

α α α α α α

α α α α

α αα α α

= + × + × + × + × + ×

+ × + × + × + ×

× + ×+ × + × + × +

15 16 17123 123jt

jt jt jt jt

A SOX

DELTA SOX VEGA SFAS R DELTA SFAS Rα α α ε

×

+ × × + × × + × × +

PANEL A PANEL B

DEPENDENT VARIABLE =

INVEST COEF. (T-STAT.)

DEPENDENT VARIABLE = STD_RET

COEF. (T-STAT.)

INTERCEPT 0.031 (3.91)***

0.712 (6.32)***

VEGA 0.571 (5.38)***

0.176 (6.46)***

DELTA 2.567 (4.06)***

-0.071 (-4.37)**

TENURE -0.231 (-2.12)**

-0.104 (-5.69)***

CASH_COMP 0.008 (5.59)***

-0.058 (-4.91)***

LOG_SALES -0.014 (-3.96)***

-0.114 (-8.39)***

M_B 0.009 (7.36)***

0.007 (4.22)***

SALES_GROWTH 0.004 (2.05)**

0.001 (0.96)

RETURN -0.007 (-4.62)***

-0.025 (-5.94)***

AUG00_AUG01_RET 0.018 (0.67)

-0.242 (-3.87)***

LEVERAGE 0.005 (1.42)

0.011 (1.14)

TIME 0.231 (5.07)***

0.163 (3.74)***

SOX -0.081 (-5.14)***

-0.183 (-6.26)***

SFAS123R -0.002 (-0.49)

0.002 (0.51)

VEGA × SOX -0.248 (-4.98)***

-0.194 (-4.63)***

DELTA× SOX -2.017 (-5.16)***

-0.963 (-2.42)**

47

Table 5 Contd.

VEGA × SFAS123R -0.002 (-0.83)

-0.002 (-0.39)

DELTA× SFAS123R 0.002 (0.23)

0.005 (0.85)

R-SQUARE 0.421 0.562 ***Significant at the 1% level; ** Significant at the 5% level; *Significant at the 10% level. T-statistics in parentheses are based on robust firm-clustered standard errors (Petersen, 2009). Industry control dummies are included. Table 5 presents OLS regression results corresponding to the risky investment variables. INVEST is the sum of research and development expenditures, acquisitions, and net capital expenditures (capital expenditures less sale of property, plant, and equipment) divided by average total assets; STD_RET is measured as the annualized standard deviation of daily stock returns; VEGA is the dollar change in the CEO’s wealth for a 1% change in standard deviation of returns; DELTA is the dollar change in the CEO’s wealth for a 1% change in the stock price; TENURE is the number of months the CEO has been in office; CASH_COMP is the sum of salary plus bonus; LOG_SALES is the logarithm of sales; M_B is the market-to-book ratio; SALES_GROWTH is the percentage change in sales for the year; RETURN is the cumulative 12 months returns for year t for firm j; AUG00_AUG01_RET is the decile ranking of the cumulative returns during August 2000 and August 2001 where the lowest decile corresponds to the most negative returns; TIME is the calendar year minus 1992; SOX is a dummy variable taking a value of 1 for the years 2002 through 2005; SFAS123R is a dummy variable taking the value of 1 for the year 2006.

48

TABLE 6: SIMULTANEOUS EQUATIONS (3SLS) ESTIMATION FOR RISKY INVESTMENTS, VEGA AND DELTA (1992 – 2006; N=14,604)

PANEL A:

PANEL B:

INVEST VEGA DELTA STD_RET VEGA DELTA

INTERCEPT 0.024 (4.56)***

0.029 (3.68)***

0.046 (3.19)***

0.657 (5.32)***

0.024 (3.15)***

0.041 (3.46)***

INVEST 0.176 (3.65)***

9.564 (4.01)***

0.179 (3.68)***

9.417 (3.87)***

STD_RET 0.249 (9.63)***

0.044 (3.24)***

0.253 (8.62)***

0.042 (3.56)***

VEGA 0.543 (5.61)***

3.342 (4.28)***

0.181 (5.77)***

3.386 (4.79)***

DELTA 2.641 (4.18)***

0.037 (3.59)***

-0.58 (-3.94)***

0.034 (3.95)***

TENURE -0.237 (-2.04)**

0.037 (3.65)***

-0.098 (-4.84)***

0.039 (4.02)***

CASH_COMP 0.007 (3.68)***

0.034 (14.36)***

0.028 (8.73)***

-0.051 (-5.19)***

0.036 (12.37)***

0.021 (7.64)***

LOG_SALES -0.012 (-3.52)***

0.045 (12.19)***

0.293 (16.34)***

-0.107 (-7.39)***

0.042 (10.49)***

0.272 (14.39)***

M_B 0.007 (4.67)***

0.006 (4.38)***

0.149 (10.26)***

0.006 (4.53)***

0.005 (3.394)***

0.137 (8.92)***

CASH 0.143 (3.86)***

-1.964 (-3.69)***

0.041 (5.61)***

-1.863 (-4.21)***

RETURN -0.006 (-5.39)***

0.346 (4.51)***

0.297 (4.92)***

-0.028 (-5.73)***

0.354 (3.96)***

0.286 (4.23)***

SALES_GROWTH 0.003 (1.78)*

0.002 (0.84)

AUG00_AUG01_RET 0.004 (0.62)

0.002 (0.37)

-0.004 (-0.71)

-0.249 (-4.02)***

0.002 (0.49)

-0.003 (-0.86)

LEVERAGE 0.004 (0.82)

-0.004 (-0.83)

-0.145 (-3.21)***

0.013 (1.03)

-0.003 (-0.64)

-0.131 (-3.54)***

TIME 0.234 (4.83)***

11.859 (5.91)***

82.64 (4.53)***

0.159 (3.87)***

11.746 (5.34)***

84.37 (5.07)***

49

Table 6, contd.

SOX -0.078 (-4.31)***

-6.834 (-5.01)***

-52.95 (-3.71)***

-0.179 (-6.14)***

-6.738 (-4.61)***

-53.68 (-4.81)***

SFAS123R -0.002 (-0.35)

-0.004 (-0.57)

0.002 (0.56)

0.001 (0.48)

-0.003 (-0.46)

0.001 (0.27)

INVEST × SOX -0.037

(-4.61)*** -5.743

(-3.48)*** -0.035

(4.52)*** -5.671

(-3.33)***

STD_RET × SOX -0.052 (-5.79)***

-5.863 (-4.27)***

-0.049 (-5.33)***

-5.918 (-5.29)***

INVEST × SFAS123R -0.004 (-0.69)

0.003 (0.78)

-0.003 (-0.26)

0.004 (0.52)

STD_RET× SFAS123R -0.003 (-0.84)

0.002 (1.04)

-0.002 (-0.47)

0.003 (0.93)

VEGA × SOX -0.256 (-5.17)***

-0.183 (-4.56)***

DELTA× SOX -2.154 (-4.87)***

-0.916 (-2.41)**

VEGA × SFAS123R -0.001 (-0.74)

-0.002 (-0.83)

DELTA× SFAS123R 0.003 (0.15)

0.004 (0.58)

R-SQUARE 0.442 0.418 0.395 0.584 0.424 0.399

***Significant at the 1% level; ** Significant at the 5% level; *Significant at the 10% level. T-statistics in parentheses are based on robust firm-clustered standard errors (Petersen, 2009). Industry control dummies are included. Table 6 presents 3 stage OLS regression results (3 SLS) corresponding to the risky investment variables and managerial incentives. INVEST is the sum of research and development expenditures, acquisitions, and net capital expenditures (capital expenditures less sale of property, plant, and equipment) divided by average total assets; STD_RET is measured as the annualized standard deviation of daily stock returns; VEGA is the dollar change in the CEO’s wealth for a 1% change in standard deviation of returns; DELTA is the dollar change in the CEO’s wealth for a 1% change in the stock price; TENURE is the number of months the CEO has been in office; CASH_COMP is the sum of salary plus bonus; LOG_SALES is the logarithm of sales; M_B is the market-to-book ratio; CASH is the cash available at the end of the period deflated by total assets; SALES_GROWTH is the percentage change in sales for the year; RETURN is the cumulative 12 months returns for year t for firm j; AUG00_AUG01_RET is the decile ranking of the cumulative returns during August 2000 and August 2001 where the lowest decile corresponds to the most negative returns; LEVERAGE is the firm’s total debt divided by total assets TIME is the calendar year minus 1992; SOX is a dummy variable taking a value of 1 for the years 2002 through 2005; SFAS123R is a dummy variable taking the value of 1 for the year 2006.