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Managerial discretion, motivation, and Stock Option Assumptions

Xiaoyan Cheng College of Business Administration University of Nebraska-Omaha Omaha, NE, 68182

David Smith School of Accountancy University of Nebraska-Lincoln Lincoln, NE, 68588

October 28, 2009 Managerial discretion, motivation, and Stock Option Assumptions

Abstract

This paper provides evidence for the debate whether managers’ discretion, incentives, and accuracy of stock option estimates differ under the recognition and disclosure reporting regimes for those firms voluntarily choosing to recognize stock options expense versus those mandatorily forced to do so. We find that firms who wait for mandatory adoption of the recognition regime after the effective date of SFAS 123R understate option expenses to a larger extent. Our test results suggest that managerial opportunism accounts for these understatements. In addition, we find that the amount of managerial discretion over stock option estimates in the mandatory group is lower than in the voluntary group, and the accuracy of option estimates in the mandatory group is higher than that in the voluntary group. Our interpretation for such phenomena is that although mandatory firms have the tendency to understate option value, the magnitude of such deviation is much lower than the amount that voluntary firms deviate from option estimates, thus resulting in a higher accuracy. Our findings support the argument made by

Hodder et al. (2006) that accuracy is a function of the amount of managerial discretion.

2 Managerial discretion, motivation, and Stock Option Assumptions

1. Introduction

In December 2004, the FASB issued SFAS No. 123 (revised 2004) (SFAS No.

123R), Share-Based Payment, that addresses the accounting for share-based payment transactions. SFAS No. 123R eliminates firms’ ability to account for share-based compensation transactions using the intrinsic value method under Accounting Principles

Board (APB) Opinion No. 25, Accounting for Stock Issued to Employees. Instead it requires stock option expenses be accounted for using a fair-value-based method and recognized in the income statement. SFAS No. 123R is effective for companies beginning in the first quarter of fiscal 2006.

Although SFAS No.123R is a conservative accounting treatment, it gives managers considerable latitude in determining stock option model input choices. The broad objectives of this paper are to examine whether the new accounting standard affects managerial discretion over stock option estimates and to explore underlying motivations and subsequent consequences in terms of accuracy. Specifically, this paper provides evidence whether managerial discretion over model input choices, managers’ incentives, and accuracy of stock option estimates differs under recognition and disclosure reporting regimes. When examining the relations between both managerial discretion and accuracy of stock option estimates and the change of accounting regulation, it is important to distinguish voluntarily expensing firms from mandatorily expensing firms. 1The effect of mandatorily expensing may differ from voluntarily expensing because underlying motivations are different for these two groups. Holthausen (1990) documents three

1 Mandatorily expensing firms fit the situation in which management is forced to use fair value method to account for stock options. 3 alternative, but not mutually exclusive, motivations for choosing accounting methods.

These are the opportunistic behavior, efficient contracting, and information perspectives.

For example, Amir and Ziv (1997) examine the timing of adoption of SFAS106:

Employers’ Accounting for Post-retirement Benefits other than Pensions and argue that managers have private information and use the adoption timing and recognition/disclosure choices to convey this information to investors.2 The essence of

Amir and Ziv’s paper is that firms trade-off early or late adoption of an accounting standard; it finds that early adoption conveys private good news. Aboody, Barth, and

Kasznik (2004) find that the timing of adoption of expensing stock options is related to the private incentives of top management and members of the board of directors.

Managers are more likely to voluntarily adopt fair value method if they believe early adoption conveys their commitment for increased transparent reporting and this signal reduces information asymmetry. This study extends prior research by documenting how the choice of timing of adoption affects managerial discretion and accuracy of stock option estimates and what managers’ incentives contribute to the changes of managerial discretion and accuracy in stock option estimates from the pre to post expensing periods.

To address the objectives of this paper, we investigate the following three research questions. First we investigate whether managers exercise differential discretion in estimating option expenses between voluntary and mandatory firms. Manager’s discretion is measured as the difference between the option value recorded using Black

Scholes model and the nondiscretionary component of option value, which is evaluated based on historic experience and industry benchmarks. The discretionary component of

2 Amir and Ziv (1997) find that firms with favorable information and smaller postretirement benefit liability are more likely to voluntarily recognize liability early, while firms with unfavorable information and larger liability are more likely to wait until mandatory adoption date.

4 option value, which cannot be explained by the historical experience and industrial benchmark, is most likely driven by managerial discretion.

Our second research question addresses the impact of SFAS123R on the manager’s discretion on option estimates and identifies managers’ underlying motivations for exercising differential discretion under different reporting regimes. Empirical evidence from previous studies (Hodder et al. 2006) documents that information and opportunistic incentives jointly determine managers’ use of model input choices. By relating manager’s discretionary component of stock option expense to proxies for managers’ incentives during pre and post expensing periods, this study examines which of the two incentives contribute to the changes in manager’s discretion on stock option expenses in the mandatory group.

Our third research question investigates subsequent consequences of expensing stock options. We use the accuracy of stock option estimates to measure information reliability and divide our third question into two parts: (1) How does the accuracy of stock option estimates differ between mandatory and voluntary firms? (2) Could information or opportunistic incentives explain the change of accuracy of stock option estimates after the adoption of SFAS123R?

Overall, we find that mandatory firms have a tendency to understate option estimates. Specifically, firms who wait for mandatory adoption understate option expense to a larger extent under recognition regime and managerial opportunism accounts for such understatement after the adoption of SFAS123R.3 The tendency to manipulate stock- based compensation expense downward in the mandatory firms, especially in the post

3 Recognition regime refers to recognizing stock option expenses on the income statement, and disclosure regime refers to disclosing stock option expense in the footnotes. 5 expensing period, could be driven by the cost of recognition consideration. Our findings also provide insights in documenting the relation between managerial discretion and accuracy. We find that there is an improvement in accuracy in mandatory firms after the adoption of SFAS123R. However, none of the compensation and informational incentives explains this. The improvement in accuracy after the adoption of SFAS123R in mandatory firms is partly because understatement in reported volatility in the post period corresponds to a lower ex post realized firm volatility and market volatility, implying that accuracy is related to the direction of managerial discretion. Furthermore, we find that the amount of managerial discretion over stock option estimates in the mandatory group is lower than in the voluntary group, and the accuracy of option estimates in the mandatory group is higher than that in the voluntary group. Our interpretation for such phenomena is that although mandatory firms have the tendency to understate option value, the magnitude of such deviation is much lower than the amount that voluntary firms deviate from option estimates, thus resulting in a higher accuracy. Our findings support the argument made by Hodder et al. (2006) that accuracy is a function of the amount of managerial discretion. We find that the larger the amount of managerial discretion, the lower the accuracy.

This paper makes several contributions to the current literature. First, mandatorily and voluntarily recognizing stock option expenses have different implications. Using a sample that separates voluntary and mandatory expensing stock options enables us to investigate the differential managerial behavior about stock option estimates and examine whether managers treat stock option expenses differently under disclosure and reporting regimes. Second, this paper extends previous research by

6 documenting that the cost of recognition of option expenses is higher in the mandatory firms. Dechow et al (1997) use comment letters to show higher recognition cost associated with those firms opposing mandatorily expensing stock options. This study identifies the actual mandatory firms and provides direct evidence regarding a higher recognition cost in the mandatory firms. Third, we offer new evidence on the questions of whether government can play a useful role in regulating accounting standards and whether the choice of accounting method affects managerial discretion and accuracy of stock option estimates. By investigating the relation between managerial discretion and accuracy, this study provides evidence in documenting that the new accounting standard encourages managers to exercise their discretion by improving accuracy. Understanding the effect of accounting regulation is important to help regulators and practitioners decide whether mandatory expensing of stock options is a preferable choice.

The remainder of the paper is divided into the following sections. Section 2 is the background and section 3 contains the hypothesis development. Section 4 is the sample selection and descriptive statistics. Section 5 describes the methodology and results. This is followed by the summary in section 6.

2. Background

In 1995, the Financial Accounting Standards Board (FASB) passed the Statement of Financial Accounting Standards (SFAS) No. 123, Accounting for Stock-Based

Compensation. Under SFAS123, firms may choose to measure stock-based compensation either using a fair value method or intrinsic value method specified by Accounting

Principles Board (APB) Opinion No.25.4 While the FASB encouraged firms to use the 4 Under APB25, stock-based compensation is recognized only when stock price exceeds exercise price on the measurement date, which is referred as the intrinsic value method. Since most firms set the exercise price equal to stock price, no stock-based compensation cost is reflected in income statements for option grants. Under the fair value method, stock option expenses are estimated using option-pricing models that 7 fair value method, prior to 2002 most firms chose to account for stock-based compensation using the intrinsic value method and to disclose in the footnotes with pro- forma effect as if the company had applied the fair value recognition provisions of

SFAS123. Starting in January 2003, more and more firms began to voluntarily expense stock options. The early adoption of the fair value method is a response to a wave of accounting scandals that highlighted a need for increased conservatism with regards to employee stock option expenses. In 2002, the FASB issued SFAS148, Accounting for

Stock-Based Compensation—Transition and Disclosure, which amends SFAS 123 to provide transition guidance from the intrinsic value method to the fair value method.

Under SFAS148, firms can choose either a “prospective,” a “modified prospective,” or a

“retroactive restatement” transition method.5 On December 16, 2004, the FASB issued a revised standard, SFAS 123R (2004), Share- Based Payment, with an effective date of

2006. This new standard requires that all firms use the fair value method to account for stock option compensation and eliminates firms’ ability to account for share-based compensation transactions under the intrinsic-value method utilizing APB Opinion No.

25.6 The passage of SFAS123R is one of the most debated issues in accounting history. include four inputs expected option life, expected stock price volatility, expected dividend yield, and the risk-free interest rate. Stock-based compensation expense is recognized and reported even if exercise price is equal to stock price. 5 Prospective transition method requires options granted in the current year be recognized as expense, which creates a one time increase in compensation expense. This method is easy to apply, but it lacks consistency with prior-period amounts and comparability with other companies. Beginning December 15, 2003, companies cannot use the prospective transition method when adopting the fair value method. Modified prospective transition method is similar to the prospective method. The only difference is that stock-based compensation would have been recognized had the fair value method been applied since the effective date of SFAS 123 (fiscal years beginning after December 15, 1994). Under the modified prospective approach, if a company adopted the fair value method in January 2003, stock-based compensation reported in 2003 has two components: an estimate of the fair value of option grants issued in 2003 and an estimate of the fair value of option grants issued between 1995 and 2002 that have not expired (Moehrle 2004). Retroactive method requires prior years’ financial statements would be restated as if the fair value method had been applied since 1995.

6 For most public entities, SFAS123R was effective as of the beginning of the first interim or annual reporting period that begins after June 15, 2005. For small and nonpublic entities, they have to adopt

8 Many firms opposed mandatorily expensing stock options, arguing recognizing option compensation in income would result in increased contracting costs and thus negatively affect stock prices. The FASB lists four reasons for issuing this statement: addressing concerns of users and others, improving the comparability of reported financial information by eliminating alternative accounting methods, simplifying U.S. GAAP, and converging with international accounting standards. As stated by FASB, the purpose of this standard is to truly recognize the cost of stock-based compensation and reflect the economic consequences in the financial statements. The evolution of accounting standards for stock-based compensation is from disclosure in footnotes to voluntarily expensing, and then to mandatory recognition in the income statement.

3. Hypothesis development

Empirical findings using pre-SFAS 123R footnote disclosures suggest that managers exercise discretion in valuing stock options. Aboody et al. (2006) find that firms understate stock-based compensation expense disclosed in the footnotes under

SFAS 123 to increase investors’ perceived profitability and decrease investors’ perceived excessive compensation. They collect stock option expenses from firms’ footnote disclosure from 1996 to 2001 and focus on the four key option pricing model inputs: expected option life, expected stock price volatility, expected dividend yield, and the risk- free interest rate. Their results are strongest for option life and stock price volatility, suggesting managers have greater latitude in these two inputs when determining stock option expenses. Hodder et al. (2006) examines managerial discretion using stock option data from 1995 to 1998, deleting those observations with pre-SFAS123 adoption. Hodder

SFAS123R as of the beginning of the first annual reporting period that begins after December 15, 2005. (FASB 2004) 9 et al. (2006) finds that opportunistic and information incentives jointly explain the accuracy of stock option estimates. Johnston (2006) documents that firms voluntarily expense stock options tend to manage option-pricing model inputs to bias option estimates downward more than disclosing firms without the recognition of option expenses. Overall, previous studies choose sample firms either using APB 25 intrinsic value method recognition with footnote disclosure or focus on firms that voluntarily expense stock options. Our study differs from these previous papers in two ways. First we examine whether mandatory recognition of stock option expense affects managerial behavior. Second, we compare the magnitude of managerial discretion and subsequent consequences in terms of accuracy for stock option expense recognition by mandatory versus voluntary groups.

a. Stock Option Valuation Assumptions and Executive Compensation

Previous studies document potential differential firm characteristics between firms that voluntarily adopt to expense stock options and firms that wait to be forced by

SFAS 123R to mandatorily adopt the expense method.7 Robinson and Burton (2004) find that the magnitude of stock option expense and the impact of stock option expense on profitability are significantly lower for voluntarily adopting firms. Dechow et al. (1997) suggest that top executives of firms submitting comment letters opposing mandatory expensing receive a higher proportion of their compensation from options and their firms use options more intensively for top-executive compensation. This previous stock option research implies that companies trade off benefits and costs when they decide to adopt the fair value method early or late. Firms voluntarily choosing to recognize stock option

7 Since SFAS 123R was not effective until the first quarter of fiscal 2006, the research in this paragraph was conducted prior to the mandatory requirement to expense stock options but after some companies had voluntarily agreed to follow the expense method.

10 expenses in income statement rather than footnotes perceive that the benefits of doing so outweigh the costs. This research suggests that one potential benefit from voluntarily expensing stock options is that it may signal managers’ commitment to improve financial transparency, while recognizing stock option expenses has a potential “cost” because of its impact on firm profitability. We argue, following the logic from Dechow et al., that the cost of stock option expense recognition differs between the mandatory and voluntary groups because the mandatory group firms have a higher magnitude of stock option expenses. This higher magnitude of stock option expenses could lead to the understatement of option estimates. Based on this line of reasoning, our first hypothesis stated in the alternative form is the following:

H1a: Mandatory firms have a tendency to understate option model estimates.

H1b: The magnitude of mandatory firms’ understatements of option model estimates is positively associated with the portion of compensation from stock options.

The passage of SFAS 123R, which means that all companies must now expense stock options, primarily impacts mandatory adopting firms that previously chose not to expense stock options. This potential impact is supported by Dechow et al. (1997), which suggests that disclosure in footnotes cannot be regarded as a substitute for recognition; otherwise firms would not oppose mandatory recognition of stock option expenses and accept mandatory disclosure of the stock option cost. The Dechow et al. conclusion is consistent with past studies documenting that recognized items and disclosed items are valued differently by the capital market. 8 Davis-Friday et al. (1999) find that investors assign a greater weight to recognized liabilities than to disclosed liabilities. Zhang (2005)

8 FASB Concepts Statement No. 5 defines recognition as the “depiction of an item in both words and numbers, with the amount included in the totals of the financial statements”. Schipper (2007) suggests that disclosure would be sufficient for sophisticated users, but not for unsophisticated users. 11 documents that investors value stock option reported expense under the recognition regime more as an expense than under the disclosure regime. In order to minimize the impact of expensing stock options under SFAS 123R, we argue that mandatory expensing firms exhibit differential managerial discretion for stock option estimates between the pre and post adoption SFAS 123R periods. This reasoning leads to our second hypothesis stated in the alternative form is the following:

H2: Firms that wait to expense stock options until it is mandatory will understate stock option expense in the post period.

b. What Company Incentives are Consistent with the Understatement of Stock Options Expense in the Post SFAS 123R Period?

One of the objectives of this study is to identify which factors explain differential managers’ discretion over option estimates during the pre and post expensing periods. Following previous research, we identify two incentives for firms to understate stock option estimates. The first is referred to as a managerial opportunism perspective.

The logic of this perspective is as follows. Managerial discretion associated with stock option estimates, like other accounting accruals, is a way to avoid an earnings decrease.

However, other accounting accruals will reverse in subsequent periods, so that managerial manipulation to increase earnings in one accounting period would result in a decrease of earnings in subsequent accounting periods. Managerial discretion associated with stock option estimates is a one-time practice, which is determined on the option grant date. Estimated stock option values are not adjusted in later periods, so understatement of stock option estimates could be used to boost short-term earnings.

Managers find that firm profitability would be higher with an understatement in stock

12 option expenses without the repercussions on future earnings associated with other accruals.

Managerial opportunism perspective is consistent with management’s incentive to minimize investors’ perceived excessiveness of executive compensation and so to reduce criticism of their compensation practices (Aboody et al. 2006, Hodder et al. 2006).

Aboody et al (2006) find that understatement of stock option estimates is positively related to the proxy for excessive compensation, since excessive compensation is more likely to attract media and investor attention. Brown and Lee (2007) show that after the issuance of SFAS123R, firms cut back the use of stock options and at the same time, these firms also experienced a decrease in abnormal compensation, suggesting that option cutbacks may mitigate the excessive compensation. This is probably because mandatory recognition of stock option expenses makes excessive compensation more transparent and the new accounting standard raises serious concerns about excessive compensation and profitability to mandatory adopting firms. Therefore, managers have incentives to decrease abnormal compensation and understate stock option expenses simultaneously in the post period. We expect to see that managerial discretion on option estimates in the post period is positively correlated with excessive compensation.

The second incentive to understate stock option expenses is called the information communication perspective. Managerial discretion on stock option estimates conveys managers’ private information to outside investors. Such private information relates to firms’ future economic condition, such as future operating and financial risk. Managerial discretion associated with Black-Scholes model inputs reflects manager’s anticipation regarding future operating and investing activities. A lower reported volatility than

13 historic or industry benchmarks could signal a lower future operating or financial risk

(Hodder et al. 2006). We argue both of these two incentives could explain managerial discretion associated with stock option estimates. Therefore, our third hypothesis stated in the alternative form is the following:

H3a: Managerial discretion over option estimates in the post period is positively correlated with excessive compensation (Managerial opportunism).

H3b: Managerial discretion over option estimates in the post period is positively correlated with future financial and operating risk (Information communication).

c. Accuracy of Stock Option Estimates: Voluntary versus Mandatory Expensing

Groups

To investigate subsequent consequence of managerial discretion, we use accuracy to measure information reliability.9 Hodder et al. (2006) distinguish accuracy from discretion and develop a measure to verify stock option estimate. They use an example to illustrate the concept of accuracy. The accuracy of forecasted EPS (earnings per share) is estimated by comparing the forecasted EPS to actual EPS in subsequent earnings announcement. With the same logic, they use available ex post realizations of the model inputs to obtain a measure of realized stock option expense and then they compare to reported option value. The difference between ex post realized value and reported value is equivalent to the prediction error, 10 which is used to capture accuracy. In this study, we

9 FASB’s conceptual framework states reliability of information as a primary characteristic. Reliability is defined as free from error and the assurance that the measure is represented authentically. Reliability is also divided into three ingredients: verifiability, neutrality and representational accuracy. Accuracy provides a measure to check verifiability.

10 Hodder et al. (2006)’s measurement of accuracy is developed from the estimation of analyst forecast errors.

14 apply Hodder et al. (2006)’s measurement of accuracy in examining the consequence of managerial discretion.

Previous studies explore the relation between discretion and accuracy and suggest that managers may use their discretion either to worsen or improve accuracy. Bartov et al.

(2004) find that discretion worsens accuracy when an understatement in reported volatility is not matched with the ex post realized volatility. Hirst et al. (2003) argues that managers may use their discretion to improve accuracy. The purpose for doing so is to obtain a reputation of a higher financial reporting quality, thus enjoying a lower cost of capital. However, whether managerial discretion worsens or improves accuracy remains an empirical question. Hodder et al. (2006) suggests that accuracy is not only a function of the magnitude that reported fair value deviates from the predicted value, but also related to the direction of the deviation. Since the amount of managerial discretion correlates with accuracy and differential managers’ discretion over stock option estimates exists in these two groups, the accuracy of option estimates may also differ. Therefore, our fourth hypothesis stated in the alternative form is the following:

H4: The accuracy of option estimates will differ between mandatorily and voluntarily expensing firms.

15 d. Does Option Estimate Accuracy Improve or Deteriorate in the Post SFAS 123R Period?

To further investigate the impact of SFAS123R on accuracy of option estimates, we need to consider the direction of deviation that reported fair value diverges from the predicted value. If the understatement in reported volatility corresponds to a lower ex post realized volatility, the accuracy of option estimates will be improved. Hodder et al.

(2006) use compensation and information incentives to explain the accuracy of option estimates. An improved accuracy is associated with a more accurate estimate of Black-

Scholes model inputs with the considerations of future economic conditions. Accuracy is negatively associated with managerial incentives to increase firm profitability and minimize investors’ perceived excessiveness of executive compensation without considering the ex post realized value of Black-Scholes model inputs. Therefore, if the new accounting standards SFAS123R make managers respond more to opportunistic

(information) incentives, stock option estimates would be less (more) accurate. Our fifth hypothesis stated in the alternative form is the following:

H5a: The accuracy of option estimates is improved in the post period

(Information Communication).

H5b: The accuracy of option estimates deteriorates in the post period

(Managerial Opportunism).

4. Sample selection and Description

a. Selection

Using a sample from the S&P 500 firms, we select firm-year observations covering the 2001 to 2008 time period. The firm-year observations are divided into pre expensing and post expensing groups on a firm-by-firm basis. For example, the pre expensing

16 periods for the voluntary firms include t-1 and t-2, where t is the year when firms voluntarily adopted the fair value method. The post expensing periods for voluntary firms include t, t+1, and t+2. Most voluntary firms became early adopters in 2003 and 2004; therefore, our observation period (both pre and post expensing periods) is from 2001 to

2006. For mandatory firms, we use years 2004 and 2005 to represent the pre expensing periods and years 2006, 2007 and 2008 to indicate the post period, since most firms mandatorily recognize stock option expenses starting from 2006.

We gather the option-pricing inputs from several sources. For most years we download the option-pricing model inputs from Compustat. We also hand collect some model inputs from 10K footnotes, because Compustat does not provide complete model inputs data in years 2003 and 2004.

Our initial sample begins with 499 firms. We eliminate 17 firms and 39 firms with missing option plans and with one or more missing inputs, respectively. We also exclude

24 firms that have less than six industry participants, 19 firms with insufficient CRSP data to calculate historic volatility, 22 firms with insufficient CRSP data to calculate ex post volatility, and 69 firms with missing regression variables from Compustat and

Execucomp. Finally, we delete 69 firms with less than five years of observations in order to get a reliable comparison of managerial discretion over option expenses across the pre and post periods. Thus, each sample firm has two years of observations in the pre period and three years of observations in the post period. Table 1 (Panel A) describes our sample selection. Our final sample comprises 240 firms. Eighty-one firms chose to voluntarily expense stock options and 159 began expensing options once it became mandatory.

17 b. Description

To ensure our final sample is representative of the S&P 500 firms, we compare

firm characteristics (growth opportunities, firm size, firm profitability, and industry

distribution) between our final and initial firms. Untabulated results show that the final

and initial firms do not have significant differences in growth opportunities, firm size,

and firm profitability. Furthermore, both of these groups exhibit a similar pattern in

industry distribution. Overall, such results support the representativeness of our final

sample firms.

Panel B shows the distribution of our final 81 firms which voluntarily expense by

year. From Panel B, we can see that most voluntary firms became early adopters in 2003

and 2004. Panel C compares industry distribution between voluntary and mandatory

expensing firms.11 Most notably, in the voluntary group, 35 of the 81 firms operate in the

financial service industries. This concentration is consistent with previous findings

(Bastian et al. 2003). Schroeder (2002) attributes such concentration to a joint decision

made by members of the Financial Services Forum in 2002 to expense stock options. In

the mandatory group, the percentage representations of pharmaceutical products,

telecommunications, and electronic equipment are significantly higher than those in the

voluntary group. Such concentration in the mandatory group is consistent with Dechow’s

(2004) findings that the likelihood of submitting comment letters opposing mandatory

expensing is related to the use of stock options and technology firms rely heavily on

option compensation to provide incentives.

11 We use Fama and French (1997) industry classification to assign firms to 48 industries based on four- digit SIC codes

18 Table 2 reports firm characteristics, reported model inputs, and usage of stock option plans between voluntary and mandatory expensing firms during pre and post expensing periods. Sample firms are profitable and have persistent growth during the observation window. The means of net income to total assets (market value) in the voluntary group are 3.6 (4.9) percent and 4.8 (5.9) percent in the pre and post expensing periods, respectively. Mandatory firms also show the similar pattern that the means of net income to total assets (market value) are 4.7 (2.1) percent and 6 (4.2) percent in the pre and post expensing periods, respectively. We use t-statistic to test the equality of these variables between the pre and post periods. Reported volatility is significantly lower in the post period in both voluntary (t = -7.44) and mandatory groups (t = -5.32), while the reported risk-free rate in the post period is significantly lower only for the mandatory group (t = -6.64). In the voluntary group, the reported risk-free rate in the post period is significantly positive (t = 21.9). The univariate analysis indicates that mandatory firms are more likely to understate option value in the post expensing period, since option value decreases as expected price volatility and reported risk-free rate decrease.

Table 3 presents the recognition cost in mandatory and voluntary firms before the adoption of expensing stock options. We use two measures to proxy the recognition cost: usage of stock options (calculated as the number of options outstanding divided by total common stock outstanding) and stock options expenses (calculated as the total fair value of options granted, divided by shareholders’ equity). The means of the usage of stock options and stock option expenses are 8.7% and 11.88 % (6.3% and 5.9%) in mandatory firms (voluntary firms). The results of table 3 support the argument that recognition cost

19 in mandatory firms is significantly higher than in voluntary firms (t = 5.4 in usage of stock options and t = 2.76 in stock option expenses)

5. Methodology and results a. Measures of management discretion

In order to test our first hypothesis, we have to define our measures of managerial discretion over stock option expense and stock option expense model inputs. We estimate managerial discretion over each model input by subtracting a measure of the non- discretionary model input from the reported model input. We use Hodder et al.’s (2006) model that non-discretionary stock option expenses and model inputs are estimated based on a firm’s historic and peer group benchmarks. Each model input is regressed on its estimated non-discretionary value.

REP _ VOL = a1+ β1IND_VOL + β2HIS_VOL + ε (1.1)

REP _ LIFE = a1+ β1IND_LIFE + β2HIS_LIFE + ε (1.2) REP _ INT = a1+ β1IND_INT + β2HIS_INT + ε (1.3) REP _ DIV = a1+ β1IND_DIV + β2HIS_DIV + ε (1.4)

REP_VOL, REP_LIFE, REP_INT, and REP_DIV are reported stock return volatility, reported option life, reported risk-free interest rate, and reported dividend yield, respectively. The residual of each model represents the managerial discretion when determining stock option value. Following previous research, we estimate historic volatility as the annualized standard deviation of the natural logarithm of daily stock returns from the middle of fiscal year backwards over the reported option life, multiplied by 254, which is the number of trading days in a year.12 Historic dividend yield is estimated using the prior year’s reported dividend yield. Prior year’s reported

12 For example, Boeing Company discloses that the weighted-average estimated life of the options granted is six years in its 10-K filing in 2007. Boeing’s fiscal year ends on December 31. Therefore, we measure Boeing’s expected volatility using daily stock return over the six years prior to the middle point (June 30, 2007) of Boeing’s 2007 fiscal year.

20 option life is used to measure historic option life. Historic interest is estimated as the weighted-average zero Treasury bill interest rate with a term equal to the firm’s expected option life.13 Industry return volatility, industry dividend yield, industry option life, and industry interest rate are the contemporaneous means of each input within the same industry. We use Fama and French (1997) industry classification and require each industry to have at least six firms to ensure meaningful comparisons. Table 4 (Panel A) describes regression results of reported inputs on historic and industry benchmarks. All coefficient estimates are significantly positive with adjusted R-squared ranging from 0.41 to 0.91. We run the regression separately in mandatory and voluntary firms to control for the inherent differences between these two groups.

Table 4(Panel B) compares the means of reported inputs to historic and industry benchmarks in mandatory and voluntary groups by years. Mean reported volatility is statistically lower than mean historic volatility in these two groups (difference = -8.06% in mandatory group in adoption year and difference = -4.55% in voluntary group in adoption year), however the magnitude of the difference between reported volatility and historic volatility in the mandatory group is much larger than that in the voluntary group.

The reported option life in the mandatory group in the post expensing period is consistently lower than its industry and historic benchmarks (difference between reported and industry life = 0.04, -0.06, -0.16, -0.12, and -0.1, and difference between reported and historic life = 0.02, -0.1, -0.06, -0.02, and -0.02, in two year prior to adoption year, one year prior to adoption year, adoption year, one year following adoption year, and two years following adoption year, respectively) while the reported option life in the voluntary group does not show this pattern. Other differences do not exhibit a pattern

13 T-bill interest rate is estimated at the middle of fiscal year. 21 that managers intentionally manipulate these inputs across the observation periods and the magnitude of such difference is insignificant. The results of Panel B suggest that mandatory firms exercise greater latitude in understating stock price volatility and option life. These results are consistent with prior research (Aboody et al. (2006) and provide support for rejecting the null of H1a.

For each model input, a nondiscretionary input is defined as the fitted value from equation (1.1) through (1.4). The predicted fair value of stock options is estimated using the Black-Scholes model with predicted inputs and fiscal year-end closing stock and exercise price. We measure the reported fair value of stock options using Black-Scholes model with reported inputs and fiscal year-end closing stock and exercise price.

Discretionary fair value of options is the difference between reported fair value and predicted fair value.

Discretionary_FV = Reported_FV – Predicted_FV (2)

Negative discretionary fair values indicate understatement in stock option value.

Table 4 (panel C) presents the discretionary fair value between mandatory and voluntary groups during pre and post expensing periods. We can see that the mandatory group consistently understates option estimates in the post expensing period (0.138, -0.062,

-0.028, and -0.045 per share in one year prior to adoption year, adoption year, one year following adoption year, and two years following adoption year, respectively), while the voluntary group understates option estimates only in adoption year (0.019, -0.085, 0.075, and 0.093 per share in one year prior to adoption year, adoption year, one year following adoption year, and two years following adoption year, respectively). The findings of

Panel C suggest that managerial discretion in the mandatory group results in persistent

22 under-reporting of stock option values in the post expensing period. These results provide support for rejection of our null for hypothesis 2. b. Determinants of adoption timing

An important assumption of this paper is that the choice of timing of adoption is an exogenous decision, which affects managerial discretion and accuracy of stock option estimates. Nevertheless, the choice of timing could be an endogenous decision. To deal with this potential bias, we use a two-stage approach (Heckman 1979) and estimate a logit model by identifying the determinants of the choice of timing of adoption. The first- stage regression closely follows Dechow et al. (1996).14 Using model 3, we calculate the estimated probability of mandatory choice as an instrument for the "mandatory" dummy variable.

Mandatoryj = α0 + α1Optionj + α2FCFj + α3Dividendj + α4Leveragej + α5Sizej + εj (3)

Where mandatory is a dummy variable, equal to 1 if firms wait for late adoption.

Option is the ratio of the Black-Scholes value of the options granted to the top five executives in a given year to the total compensation granted in that year, where total compensation includes stock options, restricted stocks, salary, bonus, and cash.15 FCF is free cash flow from operations scaled by total assets. Dividend is an indicator variable

14 Dechow et al. (1996) considers the underlying determinants of the choice of timing from three perspectives that were addressed in comment letters: top-executive compensation cost, cost of capital, and contracting costs. Option is a variable to capture the intensity of stock options in total compensation. Free cash flow is used to measure the extent to which a firm is cash constrained. One of the economic consequences of expensing stock options is that increases in cost of capital could be severe for firms expecting to raise capital in the future. Dividend Constraint and Leverage capture the closeness to retained- earnings-based constraints and debt covenants, since contracting costs would be higher in those firms with tighter earnings constraints and debt covenants. 15 In general, executive pay packages contain four basic components: a base salary, an annual bonus, stock options, and long-term incentive plans (including restricted stock plans and multi-year accounting-based performance plans).

23 equal to 1 if the ratio of retained earnings to dividend paid in prior year is less than two.

Leverage is total long-term debt, scaled by total assets and size is the log of total assets.

Table 5 presents the results of multivariate analysis using logistic regressions. The coefficient α1 is significantly positive (α1 = 0.7754, p-value = 0.001), indicating mandatory firms use options intensively for top-executive compensation. Overall, the results of table 5 are consistent to Dechow et al. (1996)’s findings that the choice of timing depends on the use of stock options in top-executive compensation. c. Factors influencing management discretion associated with option estimates

Based on the prior research (Hodder et al. 2006; Aboody et al. 2006), we adopt the following model to analyze underlying factors that influence managerial discretion associated with option estimates. Our model controls for industry and years fixed effects.

Dis_FV = a1+ β1Excess_comp+ β2Option + β3ΔStd_CF_Assets+ β4ΔDebt_asset +

β5Mandatory + Mandatory * (β6Excess_comp+ β7Option +

β8Std_CF_Assets+ β9Debt_asset) + β10ROE + β11Loss + β12DivNotUp +

β13Volatility + β14Corp_Gov + β15Size +β16Industry + β17 Year + ε (4)

Dis_FV is discretionary fair value per option divided by its predicted fair value.

The treatment variable is mandatory, which is the predicted probability of mandatory choice derived from model 3. The coefficient β5 is expected to be negative and statistically different from zero, if mandatory firms understate option estimates across observation periods (H1a).

We use two proxies to capture managerial incentives to manipulate option estimates (H1b): Option and Excess_comp. Option measures the size of the option plan, which is the end of the year number of options outstanding, divided by common stock outstanding. Excess_comp is defined as abnormal compensation. We use Aboody et

24 al.’s (1999) definition of abnormal compensation which is estimated as the residual from a regression model that regresses CEO total annual compensation on proxies for firm size, performance, growth, risk, and industry membership.16 Abnormal compensation and option measure managerial opportunism. Evidence that managers with higher abnormal compensation and options are more likely to exercise their discretion to understate stock option expenses supports rejection of our null for Hypothesis 1b. For our results to provide evidence for this rejection we expect coefficients β1, β2, β6, and β7 to be negative.

The interaction terms β6 and β7 capture the impact of managerial opportunism on option estimates in the mandatory group.

Discretion on option estimates can also be viewed as a way to communicate private information to the public (Healy et al. 1993). We use change in future financial and operating risk to measure informational incentives. Change in operating risk,

ΔDebt_asset, is the one-year-ahead percentage change in liabilities to assets. Change in financial risk, ΔStd_CF_Assets, is the standard deviation of operating incomes to assets over the subsequent eight quarters less the same measure calculated over the prior eight quarters. Since managerial discretion corresponds to change in future risk, we expect β3,

β4, β8, and β9 to be positive. The interaction terms β8 and β9 capture the impact of information incentive on option estimates in the mandatory group.

16 Log(CEO_COMP)it = δ0 + δ1 log(SALES)it + δ2 BM it + δ3 ROA it + δ4 GROWTH it + δ5 RETit +δ6 1YR_VOLit +δ7INDUSTRYit + δ8YEARit + ξit (5) CEO_COMP is the total annual CEO compensation, which includes cash salary, bonus, restricted stocks, and stock options. Sales is used to proxy firm size. BM, book to market ratio, is used to measure growth opportunities. Growth, 1-year sales growth, is the proxy for investment opportunities. ROA is income before extraordinary items divided by assets, and RET is annual buy-and-hold stock return. One year ahead stock price volatility, 1YR_VOL, is controlled. I also control for industry and year effects. Untabulated statistics reveal that the coefficients on log (sales), ROA, and 1YR_VOL are significantly positive. The regression explains 36% and 52% of the variation in CEO compensation in the voluntary and mandatory firms, respectively.

25 We include various firm-specific variables in model 4 to control for other potential factors that influence managerial discretion. DivNotUp is used to capture the signaling capability of dividend projection (Hodder et al. 2006), which is equal to 1 if dividend per share this year is greater than ex post dividend per share. Loss and ROE are the other two control variables related to managerial opportunism. ROE captures firm profitability, which is income before extraordinary items scaled by market value of equity. Loss measures the incidence of loss, which is equal to 1 if there is a loss. Aboody et al. (2004) suggest that firms operating in more volatile conditions tend to have larger discretionary estimates. We use prior year stock price volatility (Volatility) to measure the impact of operating environment on managerial discretion. Recent studies also show that corporate governance influences managers’ judgments in the accounting process. Bartov et al. (2004) indicate that underreporting may be costly to do in those firms with effective corporate governance, because managers have to justify their use of option estimates to the board of directors. We use G-score (Corp_Gov) from Execucomp to measure corporate governance. Firm size (Size) is measured as the natural logarithm of sales.

Table 6 (panel A) documents regression results of managerial discretion over option value between mandatory and voluntary adopting firms. The coefficient β5 is significantly negative (p value = 0.036), suggesting that mandatory firms use more discretion in lowering option value. The coefficient (β7) of interaction term mandatory*option is also significantly negative (p value = 0.004), suggesting managers who receive a higher proportion of compensation from stock options are more likely to underreport option estimates. Overall, the results of panel A support the alternative for hypothesis 1b that mandatory firms have a tendency to understate option estimates and

26 the magnitude of understatement is positively associated with the portion of compensation from stock options. d. Model for investigating whether mandatory expensing firms understate stock option expense in the post period

We use the following regression model 6 to test hypothesis 2. Model 6 is essentially the same as model 4 except that we introduce a dummy variable “Post” to test the differential managerial discretion in the mandatory group during pre and post expensing periods.

Dis_FV = a1+ β1Excess_comp+ β2Option + β3ΔStd_CF_Assets+ β4ΔDebt_asset +

β5Post + Post * (β6Excess_comp+ β7Option + β8Std_CF_Assets+

β9Debt_asset) + β10ROE + β11Loss + β12DivNotUp + β13Volatility +

β14Corp_Gov + β15Size + β16Industry + ε (6)

Our treatment variable is post, equal to 1 if firm year is after adoption year. We expect β5 to be significantly negative, if mandatory firms understate stock option expenses in the post period (H 2).

Table 6 (panel B) presents results of managerial discretion over stock option estimates in mandatory group during pre and post expensing periods. The difference in managerial discretion between pre and post expensing periods is statistically significant

(coefficient β5 = -0.131 significant at the .003 level). These results indicate mandatory firms use more discretion to lower option value after the adoption of SFAS123R, supporting rejection of the null for our hypothesis 2. e. Tests of Managerial Opportunism versus Information Communication

Since the change of managerial discretion could be related to both compensation and informational incentives, the coefficient β6 in model 6 is expected to be positive if a

27 larger understatement in stock option expense is positively correlated with a reduction in

excessive compensation (H 3a), and coefficients β8 and β9 are expected to be positive if

information incentive accounts for an understatement of option expenses in the post

period (H 3b).

In table 6 panel B, we find that coefficient β6 associated with excessive

compensation (Excess-comp) is significant in explaining managerial discretion over ESO

fair values (p = 0.05). This result supports the alternative for hypothesis 3a. None of the

coefficients on the information incentive (H 3b) variables are significant, suggesting that

only opportunistic incentives accounts for the changes in managerial discretion over

option estimates in the post expensing period. f. Accuracy of option estimates: mandatory versus voluntary expensing firms

We use Hodder et al. (2006)’s accuracy measurement, which is the negative

absolute value difference between ex post fair value of stock option expense and its

reported fair value, to compare the accuracy of stock option expense estimates for

mandatory versus voluntary expensing firms. The negative difference represents the

absolute prediction error and is calculated as follows: 17

Accuracy = -1 * │ExPost_FV - Reported_FV│ (7)

Ex post fair value (ExPost FV) is estimated using Black-Scholes model inputs, such as ex

post volatility and dividend, reported option life and risk free rate, and current year-end

stock and exercise price.18

17 Accuracy is measured as a negative number. The larger the number, the higher the accuracy. 18 Ex post dividend is estimated as the annualized dividend yield as of the final month of the reported expected option life. Ex post volatility is the annualized standard deviation of the natural logarithm of daily stock returns from the middle of fiscal year forwards over the reported option life, multiplied by 254, which is the number of trading days in a year. Ex post volatility and dividend have to estimate extended option life. If option life extends past December 2008, ex post volatility and dividend are measured as of December 2008.

28 Since a firm’s ex post volatility could have the same shift as the whole market, as suggested by Hodder et al. (2006), we control for unanticipated market wide-volatility.

Unanticipated market wide-volatility is the difference between ex post (realized) market- wide volatility and anticipated market volatility as follows:

Unanticipated_MarketVol = ExPost_MarketVol – Anticipated_MarketVol (8)

Ex post (realized) market-wide volatility(ExPost_MarketVol) is estimated as the volatility of the S&P 500 index measured over the same time period as firm’s ex post volatility.

Anticipated market volatility (Anticipated_MarketVol) is the mean of implied volatility of an S&P index as of the fiscal year end.19 Adjusted ex post volatility (ExPost_Vol) is the difference between unadjusted ex post volatility (Unadjusted_ExPost_Vol) and unanticipated market wide volatility (Unanticipated_MarketVol) as follows:

ExPost_Vol = Unadjusted_ExPost_Vol – Unanticipated_MarketVol (9)

Table 4 (panel C) presents the accuracy of per option value between mandatory and voluntary firms during pre and post expensing periods. Mandatory firms exhibit an improvement in accuracy across observation periods (-1.08 one year prior to adoption year, -0.99 in adoption year, and -0.85 one year following adoption year), while voluntary firms do not exhibit such a pattern (-1.84 one year prior to adoption year, -2.13 in adoption year, and -2.9 one year following adoption year).

Figure 1 describes the relation between managerial discretion and accuracy of stock option estimates across the pre and post expensing periods. The amount of managerial discretion over stock option estimates in mandatory group is lower than in voluntary group, while the accuracy of option estimates in mandatory group is

19 VIX, a symbol for Chicago Board Options Exchange Volatility Index, is a popular measure of the implied volatility of S&P 500 index options, which represents the market's expectation of volatility movement over the next 30 day period. 29 significantly higher than in voluntary group. The results of figure 1 support the argument that accuracy is a function of the amount of managerial discretion. The larger amount of managerial discretion is associated with lower the accuracy, suggesting a negative relation between managerial discretion and accuracy.

To test hypothesis 4, we use the following regression Model 10. Model 10 is designed to capture underlying factors that influence the accuracy of option estimates.

Accuracy is defined in equation 7. All the other independent variables are the same as previously defined.

Accuracy = a1+ β1Excess_comp+ β2Option + β3ΔStd_CF_Assets+ β4ΔDebt_asset +

β5Mandatory + Mandatory * (β6Excess_comp+ β7Option +

β8Std_CF_Assets+ β9Debt_asset) + β10ROE + β11Loss + β12DivNotUp +

β13Volatility + β14Corp_Gov + β15Size +β16Industry + β17 Year + ε (10)

Mandatory is the predicted probability of mandatory choice derived from model

3. We expect β5 to be significantly different from zero, but we do not predict the direction of significance. Option, ROE, and Excess_comp measure the impact of managerial opportunism on the accuracy of option estimates, and ΔStd_CF_Assets and ΔDebt_asset capture the impact of information incentives on the accuracy of option estimates. We also control for other variables that may influence firms’ ability to accurately estimate stock option values (Kedia and Mozumdar 2002). Firms with more volatile operations

(Volatility) may have difficulty in assessing future variability. Accuracy increases with corporate-governance strength (Corp_Gov). Loss, dividend not up, and firm size are the other control variables. Again, industry and year are used to control for fixed effects.

Table 7 panel A reports test results for hypotheses 4. Regression models have significant explanatory power: adjusted R2 is 25.23 percent in model 9 and 19.05 percent

30 in model 10. Panel A shows the regression results of accuracy between mandatory and voluntary firms. Hypothesis 4 states that the accuracy of option estimates would differ between mandatory and voluntary expensing firms. The hypothesis is supported, as reflected in coefficient β5 in equation 10 (β5 = 3.56 significant at the <.001 level). Positive coefficient β5 also indicates the accuracy of option estimates in mandatory firms is significantly higher than in voluntary group, since accuracy is measured as a negative number. Our interpretation for such a finding is that the amount of managerial discretion over stock option estimates in the mandatory group is lower than in the voluntary group and there is a negative relation between managerial discretion and accuracy: the larger the amount of managerial discretion, the lower the accuracy. Although mandatory firms have the tendency to understate option value, the magnitude of such deviation is lower than the amount that voluntary firms deviate from option estimates, resulting in a higher accuracy in mandatory firms. g. The impact of SFAS 123R on the accuracy of option estimates

To test hypothesis 5, we use the following regression model. The difference between model 11 and 10 in that we introduce a dummy variable “Post” in model 11 to test the impact of SFAS123R on the accuracy of option estimates in mandatory firms.

Accuracy = a1+ β1Excess_comp+ β2Option + β3ΔStd_CF_Assets+ β4ΔDebt_asset +

β5Post + Post * (β6Excess_comp+ β7 Option+ β8Std_CF_Assets+

β9Debt_asset) + β10ROE + β11Loss + β12DivNotUp + β13Corp_Gov +

β14Size +β15 Industry + ε (11)

In hypothesis 5, we predict an improved accuracy is positively correlated with a much lower future financial and operating risk in the post expensing period, so we expect

31 β8 and β9 to be positive. We expect β6 and β7 to be negative, because a decreased accuracy is associated with compensation variables.

Table 7, panel B presents the regression results of accuracy of option estimates in the mandatory group between pre and post periods. Most notably, the coefficient of β5 in equation 11 is significantly positive, indicating there is an improvement in accuracy in the mandatory group after adoption of SFAS123R. However, none of the coefficients on the informational incentive and compensation variables are significant. Therefore, we do not find any evidence to support hypothesis 5. The improvement in accuracy is probably because understatement in reported volatility in the post period responds to a lower ex post realized firm volatility and market volatility.

6. Conclusions

This study examines whether the new accounting standard affects managerial discretion of stock option estimates and explores underlying motivations and subsequent consequences in terms of accuracy. The study’s findings help us understand managers’ assumptions and evaluate the reliability of stock option expenses. By separating mandatory from voluntary adopting firms, this study provides evidence regarding the differential magnitude in stock option value estimates between the two groups and addresses the question whether managers treat stock option expenses differently under disclosure and reporting regimes.

We find that a higher recognition cost is associated with those firms opposing mandatorily expensing stock options and mandatory firms have a tendency to understate option estimates. We extend prior research in suggesting that a higher magnitude of stock option expenses could lead to the understatement of option estimates. Furthermore, we

32 find that firms who wait for mandatory adoption of the recognition regime after the effective date of SFAS 123R understate option expenses to a larger extent. The reason for mandatory expensing firms exhibiting differential managerial discretion between the pre and post period is to minimize the impact of expensing stock options under SFAS

123R, supporting the argument that disclosure in footnotes cannot be regarded as a substitute for recognition. Our test results also suggest that managerial opportunism accounts for these understatements.

One of our interesting findings is that the amount of managerial discretion over stock option estimates in the mandatory group is lower than in the voluntary group, and the accuracy of option estimates in the mandatory group is higher than that in the voluntary group. Our results provide insight in documenting the relation between managerial discretion and accuracy. Accuracy is not only related to the amount of managerial discretion, but also related to the direction of managerial discretion.

Although mandatory firms have the tendency to understate option value, the magnitude of such deviation is much lower than the amount that voluntary firms deviate from option estimates, thus resulting in a higher accuracy. Finally, we find that there is an improvement in accuracy in mandatory firms after the adoption of SFAS123R. An improvement in accuracy after the adoption of SFAS123 is partly because understatement in reported volatility in the post period corresponds to a lower ex post realized firm volatility and market volatility.

These findings have implications for our understanding of the financial reporting of stock based compensation expenses under the change of the accounting treatment from footnote disclosure to expense recognition. We provide evidence to

33 policy makers to determine the consequences of expensing stock options in mandatory versus voluntary firms.

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Figure 1: The relation between managerial discretion and accuracy of stock option estimates across pre and post periods.

Horizontal axis: -2 (two years prior to adoption year); -1 (one year prior to adoption year); 0 (adoption year); 1 (one year following adoption year); 2 (two years following adoption year); Accuracy_vol: accuracy per option in voluntary firms; Accuracy_man: accuracy per option in mandatory firms; Dis_FV_vol: discretionary fair value per option in voluntary firms; Dis_FV_man: discretionary fair value per option in mandatory firms;

36 Table 1: Sample selection and distribution by year and by industry Panel A: Sample selection

Firms Mandato Volunta ry ry Total S&P 500 firms 388 111 subtotal 499 Less: Firms with no option plan in all years 15 2 subtotal 17 Less: Firms missing one or more option input 35 4 subtotal 39 Less: Firms with less than 6 industry participants 19 5 subtotal 24 Less: Firms missing ex post volatility from CRSP 20 2 subtotal 22 Less: Firms missing historic volatility from CRSP 17 2 subtotal 19 Less: Firms missing other regression variables derived from Compustat and Execucomp 62 7 subtotal 69 Less: Firms with less than 5 observation years 61 8 subtotal 69 Final Sample 159 81 Subtotal 240

- Initial mandatory firm-year observations are selected from 2004 to 2008. - Initial voluntary firm-year observations include t-2, t-1, t, t+1, and t+2, where t is the year when firm voluntarily adopted fair value method.

Panel B: Distribution of voluntarily expensing firms by year

Year Firms Percent 2002 8 9.88% 2003 58 71.60% 2004 15 18.52% Total 81 100.00%

Panel C: Industry distribution between voluntary and mandatory firms. 37 Mandatory Voluntary Firm Percent Industry s Percent Firms Food products 4 2.52% 1 1.23% Candy and Soda 2 1.26% 2 2.47% Printing and Publishing 3 1.89% 0.00% Consumer Goods 6 3.77% 2 2.47% Apparel 2 1.26% 1 1.23% Healthcare 4 2.52% 1 1.23% Medical Equipment 4 2.52% 0.00% Pharmaceutical Products 10 6.29% 0.00% Chemicals 4 2.52% 3 3.70% Construction Materials 4 2.52% 1 1.23% Construction 1 0.63% 2 2.47% Steel Works 4 2.52% 0.00% Machinery 6 3.77% 1 1.23% Electrical Equipment 3 1.89% 2 2.47% Automobiles and Trucks 2 1.26% 2 2.47% Aircraft 3 1.89% 0.00% Petroleum and Natural Gas 8 5.03% 8 9.88% Utilities 8 5.03% 6 7.41% Telecommunications 2 1.26% 0.00% Business Services 14 8.81% 3 3.70% Computers 8 5.03% 0.00% Electronic Equipment 16 10.06% 0.00% Measuring and Control Equip 6 3.77% 0.00% Business Supplies 1 0.63% 2 2.47% Transportation 2 1.26% 1 1.23% Wholesale 3 1.89% 3 3.70% Retail 14 8.81% 5 6.17% Restaurants, Hotels 2 1.26% 0.00% Banking 4 2.52% 13 16.05% Insurance 5 3.14% 9 11.11% Trading 4 2.52% 13 16.05% 159 100.00% 81 100.00%

38 Table 2: Descriptive statistics between mandatory and voluntary firms during pre and post expensing periods.

Panel A: Descriptive statistics and t-differences between pre and post periods

Pre-expensing period (162 firm-years) Lowe r Voluntary quarti Lower Media Upper firms: Mean le Median Mean Std. Dev quartile n quartile t-stat Firm Characterist ics Market value ($MM) 30549 5961 11247 32818 44682 7759 15481 39293 0.46 Growth opportunity 2.62 1.59 2.19 3.49 8.11 1.66 2.13 3.03 1.20 Net income to total assets 0.036 0.011 0.028 0.048 0.065 0.012 0.033 0.07 1.90 Net income to market value 0.049 0.031 0.053 0.059 0.081 0.048 0.063 0.084 1.28 Reported ESO model inputs Reported volatility 0.396 0.295 0.356 0.303 0.096 0.24 0.289 0.344 -7.44 Reported dividend yield 0.012 0 0.008 0.012 0.012 0 0.01 0.019 0.00 Reported 0.032 0.028 0.032 0.043 0.004 0.04 0.045 0.047 21.90 risk-free

39 rate Reported expected option life 5.124 4.095 5 5.128 1.238 4.3 5 6 0.03 ESO plan Fair value of a single option 13.2 8.82 12.25 13.49 9.25 7.76 12.04 17.18 0.32 Number of options outstanding (MM) 31.2 8 14.6 38.23 52.9 7.85 16.5 45.56 1.33 Common stock outstanding (MM) 664 130.7 258.3 628.8 854.4 159.6 331.6 682.7 -0.06

Pre-expensing period (318 firm-years) Lowe r Mandatory quarti Lower Media Upper firms: Mean le Median Mean Std. Dev quartile n quartile t-stat

40 Firm Characterist ics Market value ($MM) 16632 4443 7770 22702 37215 5840 11945 22051 1.63 Growth opportunity 3.49 1.82 2.86 3.77 8.8 1.95 2.86 4.37 0.31 Net income to total assets 0.047 0.02 0.049 0.06 0.08 0.03 0.06 0.1 1.26 Net income to market value 0.021 0.026 0.045 0.042 0.082 0.04 0.05 0.06 1.49 Reported ESO model inputs Reported volatility 0.339 0.27 0.328 0.289 0.083 0.23 0.279 0.339 -5.32 Reported dividend yield 0.018 0.006 0.011 0.021 0.016 0.007 0.019 0.033 1.73 Reported risk-free rate 0.043 0.038 0.044 0.038 0.006 0.034 0.038 0.044 -6.64 Reported expected option life 5.36 5 5 5.6 1.16 5 5.5 6 1.97 ESO plan Fair value of a single option 11.23 6.67 9.81 13.09 11.75 7.34 11.42 15.87 1.69 Number of 54 10.6 23.8 48.5 111.4 8.83 18.38 42.2 -0.46

41 options outstanding (MM) Common stock outstanding (MM) 519.5 141.6 246.7 581.5 1035.5 161.6 287.3 525.1 0.57

42 Table 3: Recognition cost between mandatory and voluntary firms

Mandatory firms Mean Std P25 Median P75 option usage 0.087 0.049 0.0518 0.081 0.11 stock option expenses 0.1188 0.24 0.036 0.072 0.142

Voluntary firms Mean Std P25 Median P75 option usage 0.063 0.039 0.033 0.058 0.086 stock option expenses 0.059 0.19 0.015 0.031 0.069 t-diff mandatory versus voluntary option usage 5.4 stock option expenses 2.76 option usage: the number of options outstanding divided by total common stock outstanding; stock options expenses: the total fair value of options granted (fair value of a single option granted multiplied by the number of options outstanding), divided by shareholders’ equity;

43 Table 4: Managerial discretion and accuracy in model inputs between mandatory and voluntary firms during pre and post expensing periods.

Panel A: Regressions of reported inputs on historic and industry benchmarks.

REP _ VOL = a1+ β1IND_VOL + β2HIS_VOL + ε (1.1)

REP _ LIFE = a1+ β1IND_LIFE + β2HIS_LIFE + ε (1.2)

REP _ INT = a1+ β1IND_INT + β2HIS_INT + ε (1.3)

REP _ DIV = a1+ β1IND_DIV + β2HIS_DIV + ε (1.4)

Model 1 Model 2 Model 3 Model 4 Predicted Risk-free Sign Volatility Dividend_Yield Option life rate Paramete p- Paramete p- Paramete p- Paramete Mandatory r value r value r value r Intercept 0.8 0.34 0.03 0.131 0.26 0.28 0.132 Historic_input Positive 0.46 <.0001 0.87 <.0001 0.32 <.0001 0.15 Industry_input Positive 0.44 <.0001 0.11 <.0001 0.62 <.0001 0.81 Adj R-square 73% 89% 41% 66% n 795

Voluntary Intercept -7.1 <.0001 -0.08 0.11 -0.31 0.17 0.06 Historic_input Positive 0.65 <.0001 0.87 <.0001 0.58 <.0001 0.03 Industry_input Positive 0.48 <.0001 0.17 <.0001 0.46 <.0001 0.95 Adj R-square 77% 91% 65% 71% n 405

44 Panel B: Comparing the means of reported inputs to historic and industry benchmarks

A d o pt io n y e ar Adoption year Adoption year Adoption Adoption year + Voluntary Group -2 -1 year +1 2 Volatility 2 7. 9 0 Reported_Vol 34.80% 33.30% 33.50% 30.70% % 3 2. 3 0 Historic_Vol 37.49% 38.50% 38.10% 35.90% % 2 9. 0 3 Industry_Vol 34.24% 34.15% 33.99% 31.52% % - 4. 5 3 Reported_Vol – Historic_Vol -2.69% -5.00% -4.55% -5.23% % - 1. 0 9 Reported_Vol – Industry_Vol 0.56% -0.67% 0.22% -0.88% %

Dividend Yield 2. 0 8 Reported_Div 1.85% 1.84% 1.90% 2.04% % 2. 0 7 Historic_Div 1.88% 1.84% 1.80% 2.14% % Industry_Div 1.96% 1.98% 2.10% 2.02% 1.

45 9 5 % 0. 0 1 Reported_Div – Historic_Div -0.02% 0.00% 0.10% -0.09% % 0. 0 9 Reported_Div – Industry_Div -0.10% -0.20% -0.19% 0.05% %

Option Life 5. 5 Reported_Life 5.56 5.35 5.60 5.59 2 5. 5 Historic_Life 5.58 5.32 5.52 5.63 4 5. Industry_Life 5.58 5.26 5.64 5.58 6 - 0. 0 1 Reported_Life – Historic_Life -0.015 0.11 0.074 -0.04 9 - 0. 0 7 Reported_Life – Industry_Life -0.018 -0.15 -0.002 0.025 6

Risk-free rate 4. 0 2 Reported_Rate 4.71% 4.07% 3.40% 3.60% % 3. 9 6 Historic_Rate 4.85% 3.96% 2.90% 3.67% % 4. 0 6 Industry_Rate 4.75% 4.02% 3.42% 3.58% % 0. 0 6 Reported_Rate – Historic_Rate -0.14% 0.09% 0.50% -0.06% % Reported_Rate – -0.04% 0.04% 0.02% 0.02% -

46 0. 0 4 Industry_Rate % 8 n 81 81 81 81 1

Adoption year Adoption year Adoption year Mandatory Group -2 -1 Adoption year +1 Adoption year +2 Volatility Reported_Vol 41.70% 36.40% 32.30% 29.70% 28.18% Historic_Vol 48.20% 43.76% 39.64% 35.20% 31.64% Industry_Vol 41.61% 36.51% 33.11% 29.86% 28.36% Reported_Vol – Historic_Vol -6.98% -7.58% -8.06% -6.00% -3.45% Reported_Vol – Industry_Vol 0.07% -0.11% -0.55% -0.08% -0.20%

Dividend Yield Reported_Div 1.05% 1.09% 1.09% 1.18% 1.14% Historic_Div 0.99% 1.12% 1.04% 1.15% 1.11% Industry_Div 1.22% 1.19% 1.17% 1.26% 1.27% Reported_Div – Historic_Div 0.06% -0.03% 0.05% 0.04% 0.03% Reported_Div – Industry_Div -0.21% -0.16% -0.10% -0.07% -0.13%

Option Life Reported_Life 5.1 5.06 4.99 5.14 5.21 Historic_Life 5.08 5.16 5.07 5.16 5.23 Industry_Life 5.06 5.09 5.15 5.23 5.3 Reported_Life – Historic_Life 0.02 -0.1 -0.08 -0.02 -0.02 Reported_Life – Industry_Life 0.04 -0.06 -0.16 -0.12 -0.1

Risk-free rate Reported_Rate 3.05% 3.43% 4.02% 4.59% 4.51% Historic_Rate 2.63% 3.65% 3.82% 4.96% 4.84%

47 Industry_Rate 3.11% 3.41% 4.01% 4.58% 4.54% Reported_Rate – Historic_Rate 0.42% -0.18% 0.19% -0.37% -0.33% Reported_Rate – Industry_Rate -0.05% 0.03% 0.00% 0.02% -0.03% n 159 159 159 159 159

Panel C: Discretionary fair value per option and accuracy of option value between mandatory and voluntary firms during pre and post expensing periods.

Adopti Adoption year Adoption year Adoption year on year Voluntary group -2 -1 Adoption year +1 +2 Mean of Fair Value Reported_FV 11.58 8.44 11.89 11.14 11.34 Predicted_FV 11.33 8.42 11.98 11.06 11.25 Discretionary_FV 0.251 0.019 -0.085 0.075 0.093 change_FV as percentage 1.86% 0.31% -2.60% 0.82% 0.88% Ex_Post_FV 9.34 6.58 9.85 8.2 8.69 Accuracy -1.99 -1.84 -2.13 -2.9 -2.56 - Accuracy as a percentage -8.34% -10.50% -11.80% -13.10% 12.06% n 81 81 81 81 81

Adop tion Adoption year Adoption year Adoption Adoption year year Mandatory group -2 -1 year +1 +2 Mean of Fair Value Reported_FV 13.25 10.83 11.15 9.33 13.83 Predicted_FV 13.2 10.69 11.21 9.36 13.87

48 - Discretionary_FV 0.054 0.138 -0.062 -0.028 0.045 - change_FV as a 0.11 percentage 0.87% 1.59% -0.88% -0.24% % Ex_Post_FV 12.19 9.61 10.22 8.51 13.19 Accuracy -1.01 -1.08 -0.99 -0.85 -0.65 - 1.88 Accuracy as a percentage -4.05% -3.80% -3.85% -2.94% % n 159 159 159 159 159

Reported_vol: reported volatility; Reported_div: reported dividend yield; Reported_life: reported option life; Reported_rate: reported risk-free interest rate; Historic_vol: the annualized standard deviation of the natural logarithm of daily stock returns from the mid of fiscal year backwards over the reported option life, multiplied by 254, which is the number of trading days in a year; Historic_ div: firm’s dividend yield in the previous fiscal year; Historic_ life: prior year’s reported option life Historic_rate: the weighted-average zero Treasury bill interest rate with a term equal to the firm’s expected option life; Industry_vol: the contemporaneous mean of reported volatility within the same industry; Industry_ div: the contemporaneous mean of reported dividend yield within the same industry; Industry_ life: the contemporaneous mean of reported option life within the same industry; Industry_rate: the contemporaneous mean of reported interest rate within the same

49 industry; Reported_FV: fair value of stock options per option using Black-Scholes model with reported model inputs and fiscal year-end closing stock and exercise price; Predicted_FV: fair value of stock options per option using Black-Scholes model with predicted model inputs and fiscal year-end closing stock and exercise price; Discretionary_FV: difference between reported fair value and predicted fair value; Dis_FV as a percentage: discretionary fair value per option divided by predicted fair value; Accuracy: absolutely negative difference between ExPost_FV and Reported_FV. ExPost_FV is per option value calculated using realized (ex post) volatility and dividend yield and reported risk-free rate and option life as well as fiscal year-end price for stock price and strike price. If option life extends past December 2008, ExPost_Div is measured as of December 2008. Accuracy as a percentage: accuracy per option value divided by reported fair value.

Table 5: Determinants of the timing of adoption

Pr (Mandatory =1) Variable Predicted sign Coefficient p-value Intercept 4.5107 <.0001

Option α1 positive 0.7754 0.001

FCF α2 negative -1.8338 0.0276

Dividend α3 positive 0.245 0.1554

Leverage α4 positive 0.3786 0.328

Size α5 negative -0.3943 <.0001 n 1200 Log-Likelihood Ratio 5 <.0001

50 Mandatory: a dummy variable, equal to 1 if firms wait for late adoption; Option: the ratio of the Black-Scholes value of the options granted to top five executives in a given year to the total compensation granted in that year; FCF: free cash flow form operations scaled by total assets; Dividend: an indicator variable equal to 1 if the ratio of retained earnings to dividend paid in prior year is less than two; Leverage: total long-term debt, scaled by total assets and size is the log of total assets.

Table 6: Regression of managerial discretion over stock option estimates on incentives.

Panel A: Regression of managerial discretion over stock option estimates between mandatory and voluntary groups.

Dis_FV = a1+ β1Excess_comp+ β2Option + β3ΔStd_CF_Assets+ β4ΔDebt_asset + β5Mandatory + Mandatory * (β6Excess_comp+ β7Option + β8Std_CF_Assets+ β9Debt_asset) + β10ROE + β11Loss + β12DivNotUp + β13Volatility + β14Corp_Gov + β15Size +β16Industry + β17 Year + ε (4)

Predicted sign Parameter estimate t-value p-value Intercept -0.1585 1.36 0.17 Compensation variables: Excess_comp Negative 0.0775 1.43 0.15 Option Negative 1.253 2.72 0.06 Informational variables: 51 ΔStd_CF_Assets Positive 0.0843 0.64 0.52 ΔDebt_asset Positive -0.0034 -0.85 0.39 Control variables: ROE Positive -0.001 -0.06 0.94 LOSS 0.0103 0.87 0.38 DivNotUp 0.026 4.23 <.0001 Volatility 0.035 2.88 0.004 Corp_Gov 0.0015 1.44 0.149 Size -0.002 -0.22 0.83 Mandatory Negative -0.018 -2.09 0.036 Mandatory*Excess_comp Negative -0.087 -1.34 0.18 Mandatory*Option Negative -1.623 -2.9 0.004 Mandatory*ΔStd_CF_Assets Positive -0.932 -0.61 0.54 Mandatory*ΔDebt_asset Positive 0.044 0.92 0.35 n 1200 Adj R square 8.60%

Panel B: Regression of managerial discretion over stock option estimates in mandatory group during pre and post periods. Dis_FV = a1+ β1Excess_comp+ β2Option + β3ΔStd_CF_Assets+ β4Δdebt_asset + β5Post + Post * (β6Excess_comp+ β7Option + β8Std_CF_Assets+ β9Debt_asset) + β10ROE + β11Loss + β12DivNotUp + β13Corp_Gov + β14Size +β15 Industry + ε (6)

Mandatory group Predicted Parameter t- sign estimate value p-value Intercept 0.61 1.74 0.08 Compensation variables:

Excess_comp β1 Negative -0.04 -0.46 0.64

Option β2 Negative -0.306 -0.39 0.69 Informational variables:

ΔStd_CF_Assets β3 Positive -0.398 -0.16 0.87

52 Δdebt_asset β4 Positive 0.001 0.42 0.67 Control variables: ROE 0.003 0.28 0.77 LOSS 0.082 0.59 0.55 DivNotUp 0.248 3.84 <.0001 Volatility 0.151 0.97 0.33 Corp_Gov 0.0013 1.52 0.12 Size -0.053 -1.76 0.07

Post β5 Negative -0.131 -2.98 0.003

Post*Excess_comp β6 Positive 0.212 1.97 0.05

Post*Option β7 1.226 0.95 0.35

Post*ΔStd_CF_Assets β8 Positive 1.696 0.59 0.55

Post*Δdebt_asset β9 Positive 0.001 0.38 0.71 n 795 Adj R square 5.79%

Dis_FV: discretionary fair value per option divided by predicted fair value; Excess_comp: the residual from equation (4) compensation. Option: the end of the year the number of options outstanding divided by common stock outstanding; Loss: a dummy variable, equal to 1 if there is a loss; ROE: income before extraordinary items scaled by market value of equity; Δdebt_asset: one-year-ahead percentage change in liabilities to assets; ΔStd_CF_Assets: the standard deviation of operating cash flows to assets over the subsequent ; eight quarters less the same measure calculated over the prior eight quarter; DivNotUp: the capability of dividend projection, which is equal to 1 if dividend per share this year is greater than ex post dividend per share; Corp_Gov: governance index score Firm size: logarithm of market value Volatility: historical stock price volatility over the prior fiscal year Post: a dummy variable, equal to 1 if fiscal year is great than adoption year

Table 7: Regression of accuracy of stock option estimates on incentives

Panel A: Regression of accuracy of stock option estimates on incentives between mandatory and voluntary firms

Accuracy = a1+ β1Excess_comp+ β2Option + β3ΔStd_CF_Assets+ β4ΔDebt_asset + β5Post + Post * (β6Excess_comp+ β7 Option+ β8Std_CF_Assets+ β9Debt_asset) + β10ROE + β11Loss + β12DivNotUp + β13Corp_Gov + β14Size +β15 Industry + ε (11)

Predicted sign Parameter estimate t-value p-value Intercept -5.933 -2.73 0.0065 Compensation variables:

53 Excess_comp Negative -1.804 -1.6 0.11 Option Negative -1.12 -1.31 0.19 Informational variables: ΔStd_CF_Assets Positive -1.485 -0.55 0.58 ΔDebt_asset Positive 0.02 0.24 0.81 Control variables: ROE Positive 0.005 0.2 0.84 LOSS 0.257 0.95 0.34 DivNotUp 0.37 2.99 0.003 Volatility -0.106 -0.43 0.66 Corp_Gov 0.033 1.5 0.13 Size 0.141 1.49 0.13 Mandatory 3.56 3.43 < 0.001 Mandatory*Excess_comp -0.108 -0.49 0.62 Mandatory*Option 1.867 1.81 0.07 Mandatory*ΔStd_CF_Assets 1.462 0.47 0.64 Mandatory*ΔDebt_asset -0.028 -0.27 0.78 n 1200 Adj R square 25.23%

Panel B: Regression of accuracy of stock option estimates over incentives in mandatory group during pre and post periods.

Accuracy = a1+ β1Excess_comp+ β2Option + β3ΔStd_CF_Assets+ β4ΔDebt_asset + β5Post + Post * (β6Excess_comp+ β7 Option+ β8Std_CF_Assets+ β9Debt_asset) + β10ROE + β11Loss + β12DivNotUp + β13Corp_Gov + β14Size +β15 Industry + ε (11)

Predicted Parameter t- sign estimate value p-value Intercept -1.557 -3.38 0.0008 Compensation variables:

Excess_comp β1 0.028 0.32 0.74

Option β2 2.46 2.19 0.029

54 Informational variables:

ΔStd_CF_Assets β3 0.195 0.1 0.91

ΔDebt_asset β4 -0.002 -0.57 0.57 Control variables: ROE 0.006 0.41 0.68 LOSS 0.126 0.69 0.49 DivNotUp 0.368 4.22 <.0001 Volatility 0.697 1.46 0.14 Corp_Gov 0.003 0.18 0.85 Size 0.003 0.08 0.94

Post β5 0.292 3.66 0.0003

Post*Excess_comp β6 -0.116 -0.87 0.38

Post*Option β7 -1.367 -0.81 0.41

Post*ΔStd_CF_Assets β8 -0.538 -0.17 0.86

Post*ΔDebt_asset β9 0.002 0.46 0.64 n 795 Adj R square 19.05%

Accuracy: absolutely negative difference between ExPost_FV and Reported_FV. ExPost_FV is per option value calculated using realized (ex post) volatility and dividend yield and reported risk-free rate and option life as well as fiscal year-end price for stock price and strike price. Excess_comp: the residual from equation (4) compensation. Option: the end of the year the number of options outstanding divided by common stock outstanding; Loss: a dummy variable, equal to 1 if there is a loss; ROE: income before extraordinary items scaled by market value of equity; ΔDebt_asset: one-year-ahead percentage change in liabilities to assets; ΔStd_CF_Assets: the standard deviation of operating cash flows to assets over the subsequent ; eight quarters less the same measure calculated over the prior eight quarter; DivNotUp: the capability of dividend projection, which is equal to 1 if dividend per share this year is greater than ex post dividend per share; Corp_Gov: governance index score Firm size: logarithm of market value Volatility: historical stock price volatility over the prior fiscal year Post: a dummy variable, equal to 1 if fiscal year is great than adoption year

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