Valuation impact of Sarbanes–Oxley: Evidence from disclosure and governance within the financial services industry

Journal of Banking & Finance 30 (2006) 989–1006 www.elsevier.com/locate/jbf

Valuation impact of Sarbanes–Oxley: Evidence from disclosure and governance within the financial services industry Aigbe Akhigbe a

a,1

, Anna D. Martin

b,*

College of Business Administration, Department of Finance, University of Akron, Akron, OH 44325, United States b Charles F. Dolan School of Business, Department of Finance, Fairfield University, Fairfield, CT 06824, United States Received 23 July 2004; accepted 6 June 2005 Available online 2 December 2005

Abstract The Sarbanes–Oxley (Sarbox) legislation aimed to reduce the opacity of financial statements and improve the integrity of financial reporting by enhancing corporate disclosure and governance practices. We estimate the valuation effects of Sarbox for firms in the financial services industry and find that, except for securities firms, these firms significantly benefited from its adoption. As hypothesized, these positive effects may be attributed to expected improvement in the transparency of the relatively opaque financial services firms. We find that the cross-sectional variation in the valuation effects can be explained by disclosure and governance characteristics. Several of the significant factors are supportive of a compliance cost hypothesis. In particular, we find that the effects were less favorable for firms with less independent audit committees, without a financial expert on the audit committee, with less financial statement footnote disclosures, with less involved CEOs, and if they were smaller. In addition, reflecting the value of stronger governance, more favorable effects occurred for firms with a greater degree of independence of the board and the board committees, when there is greater motivation and ability of board members to monitor the firm, and with a greater degree of institutional ownership. Lastly, we find the wealth effects of firms viewed as non-compliant are significantly lower than firms

*

1

Corresponding author. Tel.: +1 203 254 4000x2881; fax: +1 203 254 4105. E-mail addresses: [email protected] (A. Akhigbe), [email protected]field.edu (A.D. Martin). Tel.: +1 330 972 6883.

0378-4266/$ - see front matter Ó 2005 Elsevier B.V. All rights reserved. doi:10.1016/j.jbankfin.2005.06.002

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viewed as compliant, and the variation across the group of non-compliant firms is explained by disclosure and governance measures. Ó 2005 Elsevier B.V. All rights reserved. JEL classification: G21; G22 Keywords: Sarbanes–Oxley; Wealth effects; Financial services; Banks; Insurance companies

1. Introduction The Sarbanes–Oxley Act of 2002 (Sarbox), with its focus on corporate disclosure and governance practices, was prompted by the high profile scandals at Enron and other firms. The Act emphasizes independence of the audit committee, financial expertise within the audit committee, and improvements in the nature and timing of disclosures, among other items. While the intent of Sarbox was to improve the integrity of and reduce the opacity of financial statements, it is unclear whether there were net benefits associated with the legislation. Shareholder wealth effects surrounding the passage of Sarbox provide an assessment of the expected benefits and costs of the Act. If investors and analysts determine that these disclosure and governance requirements generate net benefits, positive valuation effects should have resulted from the adoption of Sarbox. Nonetheless, we hypothesize that the share prices of firms that were expected to incur greater compliance costs were less favorably affected by Sarbox. Certainly the concerns about the costs of compliance have been expressed in the popular press, which underscores our compliance cost hypothesis. To provide some insight as to whether Sarbanes–Oxley is expected to generate valuation effects, we draw upon the two sets of studies that focus on corporate disclosure and governance. First, previous studies document that corporate disclosure through published financial statements and other required filings are important for shareholders and analysts in assessing firm value. DeFond et al. (2004) report that adding accounting financial expertise to the audit committee, which can be viewed as ensuring higher quality disclosure, is associated with an increase in firm value. In examining risk disclosures, Jorgensen and Kirschenheiter (2003) argue that firm value is higher for those that voluntarily disclose their risks; but firm value is lower for those that unwillingly are required to disclose their risks. Bloomfield and Wilks (2000) conclude that higher quality disclosures are associated with higher stock prices. Healy et al. (1999) find a positive relationship between analyst disclosure ratings and stock returns. In evaluating the impact of the Securities Act of 1933, Stigler (1964) and Simon (1989) find that mean stock returns were not affected, indicating that both undervalued and overvalued securities adjust with better information. Second, previous studies indicate that shareholders benefit from well-governed firms as they aim to maximize firm value. Using a governance index representing shareholder rights, Gompers et al. (2003) find that stock performance is significantly correlated with better governance. Research also has shown that board independence and ownership structure are associated with firm performance. While Hermalin and Weisbach (1991) do not find a relationship between board independence and performance, Shivdasani and Yermack (1999) and Rosenstein and Wyatt (1990) show that having independent directors on the board is value enhancing. Several studies argue that managerial and board

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ownership is related to firm value, yet a nonmonotonic relation is possible (Jensen and Meckling, 1976; Morck et al., 1988; McConnell and Servaes, 1990, 1995; Hermalin and Weisbach, 1991). Furthermore, the work by Shleifer and Vishny (1986) indicates that institutional owners with large positions have incentive to actively monitor firm performance, and McConnell and Servaes (1990) detect a positive relationship between institutional ownership and firm performance. In this study, only the portfolio of securities firms does not reveal positive wealth effects surrounding the passage of Sarbanes–Oxley; portfolios of large and small banks, savings institutions, and insurance companies are found to have benefited from Sarbox.2 We attribute these net benefits to the expected improvement in the transparency of these relatively opaque segments of the financial services industry. While we find some differences in the specific disclosure and governance variables that explain the variation in wealth effects across segments, across our full sample of 201 financial services firms the wealth effects from Sarbox are significantly influenced by disclosure and governance. These relationships are evaluated in univariate and multivariate frameworks. Consistent with the compliance cost hypothesis, we find that financial services firms experienced less favorable effects with a less independent audit committee, without a financial expert on the audit committee, with less financial statement footnote disclosures, with less involved CEOs, and if they were smaller. In addition, reflecting the value of stronger governance, more favorable effects occurred for firms with a greater degree of independence of the board and board committees, when there is greater motivation and ability of board members to monitor the firm, and with a greater degree of institutional ownership. Lastly, we find the wealth effects of firms viewed as non-compliant are significantly lower than firms viewed as compliant, and the variation across the group of non-compliant firms is explained by disclosure and governance measures. 2. Focus on financial services firms To the extent that there already is sufficient control and monitoring of financial services firms, the market may determine there are little or no benefits from Sarbanes–Oxley for these firms.3 Indeed, firms in the financial services industry are highly regulated and supervised by the Federal Reserve, Federal Deposit Insurance Corporation, Comptroller of the Currency, Securities and Exchange Commission, various state agencies, etc. Thus, it is conceivable that financial services firms experienced negative wealth effects surrounding the passage of Sarbox to reflect net compliance costs. We expect that there are differential valuation effects due to the Act, depending on the opacity of the segment within the financial services industry. More specifically, we hypothesize that shareholders of more opaque segments experienced net gains from the adoption

2

Other studies also study the wealth effects of legislation within the financial services industry (e.g., Aharony et al., 1988; Cornett and Tehranian, 1989, 1990; Sundaram et al., 1992; Fraser et al., 1997; Bhargava and Fraser, 1998). 3 Consistent with the spirit of the governance and disclosure requirements that are emphasized in Sarbox, Barth et al. (2004) report that government policies encouraging corporate control by the private-sector and emphasizing accurate disclosure of information are found to be associated with greater stability and higher performance.

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Table 1 Events surrounding the passage of the Sarbanes–Oxley Act of 2002 Event

Date

Event description

1 2 3 4 5 6

4/16/2002 4/24/2002 6/18/2002 7/15/2002 7/25/2002 7/30/2002

House Financial Services Committee passed the Oxley bill House approved the Oxley bill Senate Banking Committee passed the Sarbanes bill Senate approved the Sarbanes bill House-Senate Conference Committee passed a compromise Sarbanes–Oxley bill President George W. Bush signed into law the Sarbanes–Oxley Act of 2002

This table describes six major events that represent clear movement towards the adoption of Sarbox (Public Law 107-204). We obtain the dates and descriptions from LexisNexis.

of Sarbox due to the expected increase in transparency. Similarly, shareholders of more transparent segments may have experienced net losses due to the compliance costs. The degree of opacity of segments within the financial services industry has been discussed in previous studies. Ross (1989) states that the degree of opacity ranges from transparent mutual fund organizations to the opaque insurance companies and savings and loan institutions. In illustrating a trend toward more transparent institutions, Merton (1995) endorses and slightly extends RossÕ (1989) classification to include the futures and options market, stock market, and government bond market as the most transparent institutions. Oldfield and Santomero (1997) provide a matrix to categorize many institutions according to their degree of opacity and whether their investments are actively managed. As an example, they believe banks, insurance companies and dealers are opaque, while hedge funds, mutual funds, index funds, and pension funds are more transparent. Morgan (2002) evaluates opacity by the disagreement between bond raters and asserts that the banking and insurance sectors are more opaque than the other sectors. 3. Development of the Sarbanes–Oxley Act of 2002 Most would agree that the high profile scandals at Enron and other firms prompted legislators to develop the Sarbanes–Oxley Act of 2002. As with most regulations, the actual content and assessment of legislative likelihood adjusted over time. Table 1 lists each of six major milestones and the date of occurrence that we gathered from various daily news sources in LexisNexis.4 We identify the first major milestone as April 16, 2002 when the House Financial Services Committee passed the Oxley bill (event 1). Certainly there were debates and speculation as to what this Committee would ultimately recommend, but not until a bill was passed by the Committee did the market know with certainty what the bill would contain. Similarly, when the House approved the Oxley bill on April 24, 2002 (event 2), the market was able to see an increased likelihood of the bill becoming law.

4

By selecting events that represent clear movement towards the enactment of Sarbox (i.e., passage of the bills through the various subcommittees and through Congress), we attempt to conform to the standard practice in the finance literature to measure the impact of new information. While we recognize that these six events may not be the only events related to the development of the Sarbox, we believe that they represent the major milestones in its development. Engel et al. (2004) provide a comprehensive list of event dates, including our six major milestones, related to corporate governance reform.

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On the Senate side, the Senate Banking Committee did not agree upon a reform bill until June 18, 2002 (event 3). Again, there were ongoing news reports and discussions prior to the CommitteeÕs agreement about the likelihood of the members reaching a consensus. When the Senate Banking Committee reached agreement, the content of its recommendation was established and with certainty the bill moves to the next phase of the legislative process. On July 15, 2002, the next hurdle was surpassed when the Senate approved the Sarbanes bill (event 4).5 Unlike the previous three events, there are indications in news reports prior to the full Senate vote that the bill was widely expected to pass, however the actual content was still uncertain due to various proposed amendments. Furthermore, concurrent with the Senate approval of the Sarbanes bill, it was also anticipated that the House and Senate bills would be reconciled. Nonetheless, the content of the compromise bill, the Sarbanes– Oxley bill, was not well established until it passed on July 25, 2002 (event 5). It is our belief that the major milestone when Congress reached a compromise should have provided the market with the likely content of the law and high expectation that the Sarbanes–Oxley Act of 2002 would ultimately be enacted. Nonetheless, we also include the point when Sarbox was enacted, with approval by President George W. Bush on July 20, 2002 (event 6) as it may contain residual information. 4. Data and methods The valuation effects associated with the development of the Sarbanes–Oxley Act of 2002 are examined for all financial services firms, and separately for banks, savings institutions, securities firms, and insurance companies. We classify firms into these segments based on the three-digit standard industrial classification (SIC) codes provided in the Standard and PoorÕs Compustat database. Banks are identified as firms with SIC code 602X. We further divide this group of banks into relatively large banks and relatively small banks, if the bank has total assets greater than or less than $10 billion at the end of 2001, respectively. We draw samples of savings institutions and securities firms using SIC codes 603X and 621X, respectively. Lastly, insurance companies are identified using SIC codes 631X, 632X, 633X, 635X, and 636X. We include all firms from these five segments that have the necessary CRSP stock return data, and the required data to subsequently conduct cross-sectional analyses. This sample selection approach results in a total sample of 201 financial services firms, which contains 54 large banks, 44 small banks, 19 savings institutions, 16 securities firms, and 68 insurance companies. To estimate the valuation effects associated with Sarbox, two models are used that incorporate all six major events and control for a beta shift in the post-Sarbox period similar to Bhargava and Fraser (1998). Both models are estimated for various portfolios using the seemingly unrelated regression technique developed by Johnston (1984) and daily returns from 300 days prior to the first event to 300 days following the last event.6 The first model measures the abnormal returns separately for each event j: 5 We note that on July 16, 2002 the House passed the Corporate Fraud Accountability Act. Many elements of this ultimately were included in the compromise bill. Because the three-day event window associated with event 4 already captures this date, it is not separately examined. 6 Since we have a special case where the independent variables are the same across the sector portfolios, OLS and SUR generate the same coefficient estimates.

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Rpt ¼ b0p þ b1p Rmt þ

6 X

kjp Djt þ b2p dt Rmt þ ept

ð1Þ

j¼1

where Rpt Rmt Djt dt b0 b1 kj b2 ept

portfolio return on day t market return on day t, using CRSP equally weighted market index 1 for the three days [1, +1] surrounding event j, and 0 otherwise 1 for the last event day and all subsequent days, and 0 otherwise intercept systematic risk coefficient measuring the abnormal return for event j shift in systematic risk in the post-Sarbox period error term on day t

From this model, we examine the statistical significance of each coefficient, k1 through k6. If new information is released and/or the likelihood of legislation changes over each event window, these coefficients should be statistically significant. If the market believes there is sufficient control, monitoring and transparency of financial services firms, negative abnormal returns should be revealed. In effect, negative abnormal returns indicate that the market perceived the compliance costs would exceed the benefits. Alternatively, if the market perceived the benefits outweigh the costs, then positive abnormal returns should be detected. The second model measures the average abnormal share price movement across all six events Rpt ¼ b0p þ b1p Rmt þ ccomb;p Djt þ b2p dt Rmt þ ept

ð2Þ

where ccomb, p the coefficient measuring the combined abnormal return for the six events Djt 1 for the three days [1, +1] surrounding each event j, 0 otherwise; j = 1–6 and all other variables were previously defined. In this model, we examine the ccomb coefficient to assess the overall impact of the passage of Sarbox on firms in the financial services industry. The valuation effects surrounding the development of Sarbox may vary with respect to firm-specific disclosure and governance characteristics. Thus, we evaluate the cross-sectional variation in the firm-level three-day average abnormal returns, ccomb, using the following explanatory variables, grouped as disclosure, governance, and other variables. The disclosure and governance variables are constructed using 2002 proxy statement data included in The Corporate LibraryÕs Board Analyst database, except where indicated otherwise.7 The other variables are computed from end of year 2001 Compustat and CRSP data.

7

For these variables, we in effect use 2002 data as proxies for 2001 data, since the 2001 data were frequently unavailable in this database.

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4.1. Disclosure variables To capture the integrity and opacity of financial disclosure, the variables we are able to gather are the degree of independence of the audit committee, existence of an independent financial expert on the audit committee, and degree of disclosure through financial footnotes. With the passage of Sarbox, firms are required to have independent audit committees and disclose whether they have a financial expert on their audit committee. If the firm chooses not to include a financial expert, then an explanation must be provided. The legislators anticipate that the quality of financial statements will be enhanced with better oversight and financial literacy by the audit committee. We define AUDIND as the percentage of independent directors on the audit committee and FINEXPT is set equal to one if there is an independent financial expert on the audit committee and zero otherwise. If the compliance cost hypothesis holds, firms that were not in compliance should have experienced lower valuation effects to reflect the additional costs to comply. Thus, we expect a positive relationship between abnormal returns and both, AUDIND as well as FINEXPT. Sarbox also contained increased disclosure of off-balance sheet transactions, and other information concerning changes in financial or operating conditions. As a proxy, we measure the degree of financial footnotes, FNRATIO, as the number of footnote pages scaled by the total number of pages in the 2001 annual report.8 Firms with less disclosure in footnotes may be expected to incur greater compliance costs to implement the necessary systems and organizational structure to comply. Therefore, a direct relationship between FNRATIO and abnormal returns may be detected. To reflect the compliance cost hypothesis, firms with less disclosure are expected to have experienced lower valuation effects. Table 2 provides descriptive statistics for the firm characteristics used in the cross-sectional analyses. The mean and median values are reported for the full sample of 201 financial services firms and for each of the five segments. The characteristics have been grouped together as disclosure variables, governance variables, and other variables. Here we discuss the descriptive statistics for the three disclosure variables. The mean proportion of independent audit committee members (AUDIND) is on average across the full sample quite high (86%), ranging from 80% for large banks to 96% for securities firms. There also is a high proportion of the full sample (93%) with an independent financial expert on the audit committee (FINEXPT). All the small banks and securities firms have a financial expert. Using the relative number of footnote pages in the annual report (FNRATIO) to indicate the quantity of disclosure, our sample shows that small banks and savings institutions provide the greatest amount of footnote disclosure, and insurance companies provide the least amount of footnote disclosure. 4.2. Governance variables The Sarbox legislation has a clear emphasis on strengthening governance and oversight, through its requirement of independent audit committee members, requirement of CEO and CFO certification of financial statements, establishment of the Public Company

8

We thank an anonymous reviewer for suggesting the scaled version of this variable.

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Table 2 Descriptive statistics of firm characteristics used in cross-sectional regressions for 201 financial services firms and by segment Variable

Large banks (#54)

Small banks (#44)

Savings inst. (#19)

Securities firms (#16)

Insurance cos. (#68)

Mean

Mean

Median

Mean

Median

Mean

Median

Mean

Median

Mean

Median

Median

Disclosure variables AUDIND 0.8571 FINEXPT 0.9265 FNRATIO 0.3296

1.0000 1.0000 0.3244

0.7982 0.8571 0.3380

1.0000 1.0000 0.3304

0.8740 1.0000 0.3673

1.0000 1.0000 0.3425

0.8989 0.9474 0.3606

1.0000 1.0000 0.3571

0.9575 1.0000 0.3276

1.0000 1.0000 0.2976

0.8591 0.9118 0.2896

1.0000 1.0000 0.2809

Governance variables BRDIND 0.6879 NOMIND 0.7036 COMPIND 0.8176 BRDSTOCK 0.8655 BRDCRED 0.7970 CEOINVOLV 1.1961 INST 0.5117 INSIDE 0.0758

0.7100 1.0000 1.0000 1.0000 0.8900 1.0000 0.5352 0.0500

0.7121 0.6811 0.7571 0.8588 0.7036 1.2143 0.4332 0.0569

0.7300 0.9150 1.0000 1.0000 0.8100 1.0000 0.4926 0.0221

0.6820 0.6651 0.8018 0.9604 0.8364 1.4222 0.3981 0.1057

0.6900 0.8000 1.0000 1.0000 0.8700 1.0000 0.3327 0.0668

0.6505 0.8195 0.8574 0.9132 0.9079 1.2105 0.4988 0.0832

0.6700 1.0000 1.0000 1.0000 1.0000 1.0000 0.5118 0.0707

0.6419 0.7986 0.9425 0.8544 0.9081 0.9375 0.5629 0.1139

0.6550 1.0000 1.0000 0.9200 1.0000 1.0000 0.5759 0.0747

0.6931 0.6928 0.8490 0.7975 0.7906 1.0882 0.6432 0.0605

0.7300 1.0000 1.0000 0.9100 0.8900 1.0000 0.6991 0.0340

Other variables LEV ROE MVEQUITY FASSET MVBV

0.0837 0.2629 2.3753 0.0106 1.8054

0.1215 0.3393 14.8739 0.0160 2.0215

0.1172 0.3223 6.2312 0.0120 2.0593

0.0903 0.2741 1.2256 0.0140 2.2436

0.0656 0.2788 1.0703 0.0133 2.1155

0.2376 0.2497 4.2720 0.0077 1.8229

0.2574 0.2434 1.8714 0.0071 1.7369

0.0870 0.3707 12.6740 0.0235 2.9022

0.0722 0.2449 3.3137 0.0102 1.8353

0.0686 0.2383 8.3474 0.0193 1.4372

0.0468 0.1824 3.0189 0.0064 1.2898

0.1050 0.2849 8.5278 0.0165 1.9254

The mean and median values of firms characteristics used for the independent variables in the regression analyses are reported in this table. AUDIND is the proportion of independent audit committee members, FINEXPT is 1 if independent financial expert is on the audit committee and 0 otherwise, FNRATIO is # footnote pages/total # pages in annual report, BRDIND is the proportion of independent board members, NOMIND is the proportion of independent nominating committee members, COMPIND is the proportion of independent compensation committee members, BRDSTOCK is the proportion of board members who own stock, BRDCRED is the proportion of board members with seats on other boards, CEOINVOLV is the # of high profile roles held by the CEO, INST is the proportion of institutional ownership, INSIDE is the proportion of insider ownership, LEV is LT debt/total assets, ROE is EBIT/book value of equity, MVEQUITY is the market value of equity in $ billions, FASSET is fixed assets/total assets, MVBV is market value of equity/book value of equity.

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All financial services firms (#201)

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Accounting Oversight Board, focus on conflicts of interest by securities analysts and auditing firms, as examples. To the extent that the legislative process induced a heightened awareness of governance and its value, we hypothesize that firms with stronger governance may have been rewarded. Given the emphasis on independence in Sarbox, investors during this time may have reassessed the importance of board independence. Extrapolating from the work by Shivdasani and Yermack (1999) and Rosenstein and Wyatt (1990), firms with a greater degree of board independence may have been rewarded with higher valuation effects. To capture the degree of independence of the board, we examine three variables, BRDIND, NOMIND, and COMPIND, defined as the proportion of independent board members, nominating committee members, and compensation committee members, respectively. The Board Analyst database classifies board members as independent outside (non-affiliated) directors. We then use these data to compute proportion of independent directors on the board and these board committees. We project that a positive relationship will result between these independence variables and valuation effects. The ability and motivation of the board to effectively monitor and control the decision making of the firm is also considered. Firms with more (less) credible board members were likely rewarded (penalized) if they were viewed as more strongly governed. As a proxy, we measure BRDCRED as the proportion of the board who hold seats on other boards. Credibility should be greater for directors that hold seats on other boards, since these members clearly are sought after and have further directly related experience.9 Also, to measure the degree of motivation that board members have to effectively monitor and control the firm, we use the proportion of the board that owns stock in the firm, BRDSTOCK. Detecting a direct relationship between abnormal returns and BRDCRED and BRDSTOCK would be consistent with the market rewarding firms with more effective boards. Prompted by the high profile scandal at Enron where the CEO has alleged that he was unaware of their misleading financial statements, Sarbox requires that financial statements are certified by the CEO and CFO. We predict that more (less) involved CEOs were rewarded (penalized) since they should find it easier (more difficult) to comply with the Sarbox certification requirement. Consistent with this compliance cost hypothesis, firms with less involved CEOS would be expected to incur added costs to comply, thus experience lower valuation effects. Involvement of the CEO, CEOINVOLV, is an index constructed by counting the number of high profile roles held by the CEO as a proxy for level of involvement. The roles considered are chairman of the board and memberships on the compensation, nominating, and/or audit committee. We anticipate a positive relationship between abnormal returns and CEOINVOLV.10 Ownership structure is considered important in governance studies to reflect an overall degree of monitoring and control. For ownership structure, we include two variables,

9 It is also possible that board members who sit on many boards may not effectively monitor any one firm as their time is divided across the firms, compared to board members who sit on just one board. We thank an anonymous reviewer for this alternate interpretation. 10 We also recognize a counterargument that monitoring by the board and its committees may be less effective when the CEO is overly influential due to these roles.

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INST and INSIDE. INST is defined as the proportion of shares owned by institutional investors, and INSIDE proportion of shares owned by officers and directors. The market may believe that greater monitoring in the post-Sarbox period is value enhancing. Thus, positive relationships between these ownership structure variables and abnormal returns would show that the market rewards (penalizes) firms with greater (lesser) monitoring of the firm. The summary statistics for these governance variables are displayed in Table 2. Board member independence (BRDIND) for financial services firms is approximately 64–71%, indicating there is not much variation across the segments. This range extends to 82% when looking at the independence of the nominating committee, NOMIND. The greatest degree of independence is shown for the compensation committee (COMPIND), with an average across the full sample of 82% and ranging from 76% for large banks to 94% for securities firms. The data show that, across all financial services firms, 87% of board members own stock in the firm (BRDSTOCK), ranging from 80% of insurance company board members to 96% of small bank board members. Over the full sample, 80% of the board members hold seats on other boards (BRDCRED), with a range from 70% for large banks to 91% for savings institutions and securities firms. On average, financial services CEOs hold 1.2 high profile roles (CEOINVOLV). It appears that small banks have the greatest CEO involvement (1.4 high profile roles) and securities firms have the lowest CEO involvement (0.9 high profile roles). The last two governance variables are focused on ownership structure. Table 2 shows that the average institutional ownership (INST) across all the financial services firms is 51%. The lowest degree of institutional ownership occurs within the small banks segment at 40%, while the highest degree of institutional ownership is 64% for insurance companies. Securities firms also have a relatively high institutional ownership at 56%. The average insider ownership (INSIDE) across the full sample is 8%, ranging from 6% for large banks and insurance companies to 11% for small banks and securities firms. 4.3. Other variables Summary statistics for other financial characteristics are also reported in Table 2. The variables are financial leverage (LEV), return on equity (ROE), firm size (LNSIZE), fixed assets (FASSET), and market-to-book ratio (MVBV). We compute these variables using end of 2001 Compustat data, except market values of equity are calculated using end of 2001 CRSP data. Financial leverage is long-term debt divided by total assets; ROE is earnings before interest and taxes divided by book value of equity; firm size is the natural log of the market value of equity; fixed asset ratio is fixed assets divided by total assets; and market-to-book ratio is market value of equity divided by book value of equity. Table 2 reports the average leverage of the full sample is 11%, and ranges from 7% for insurance companies to 24% for savings institutions. ROE is 28% on average and highest for large banks and securities firms, 34% and 37%, respectively. The smallest segments, based on market value of equity, are small banks and savings institutions, followed by insurance companies, securities firms, and then large banks. On average, fixed assets represent 2% of total assets with little variation across segments. Across the full sample, the market value of equity is 1.9 times the book value of equity, with the highest ratio of 2.9 for securities firms and 1.4 for insurance companies.

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5. Results Panel A of Table 3 presents the 3-day abnormal returns, kj, for each of the six events surrounding the passage of the Sarbanes–Oxley Act of 2002 from Eq. (1), while Panel B presents the average abnormal returns over all six events from Eq. (2). Across both panels, the valuation effects are estimated for several equally weighted portfolios.11 The first portfolio is comprised of all the financial services firms. The next five portfolios are comprised of the large banks, small banks, savings institutions, securities firms, and insurance companies, respectively. Additionally, we examine a portfolio of compliant firms and a portfolio of non-compliant firms. The valuation effects for non-compliant firms, in particular, provide an assessment of the net benefits from Sarbox by the firms most greatly affected by the legislation.12 As a proxy for compliance, we segment the sample on the basis of whether or not the firm has 100% audit committee independence. AUDIND as the basis for segmenting the sample is beneficial since it is a requirement of Sarbox, can be objectively measured, and it is significantly and positively correlated with all our disclosure and governance variables, except insider ownership. In both panels of Table 3, the adoption of Sarbox generated favorable effects for the portfolio of all financial services firms. Furthermore, it favorably affected four out of the five segments of the financial services industry. On July 25, 2002 when Congress passed the compromise bill (event 5 in Panel A), and on average across the events (Panel B), the portfolios of large banks, small banks, savings institutions, and insurance companies all experienced positive and statistically significant abnormal returns. The portfolio of securities firms did not benefit from any of the events, but experienced significantly negative valuation effects when the House approved the Oxley bill (event 2).13 A favorable view demonstrated by the market for the relatively opaque segments is consistent with the expectation of improved transparency. Since banks, savings institutions, and insurance companies are considered to be the most opaque (e.g., Ross, 1989; Merton, 1995; Oldfield and Santomero, 1997; Morgan, 2002), shareholders and analysts likely believed Sarbox to be value enhancing within these segments. The somewhat unfavorable stock price effects for the arguably more transparent securities firms indicate that this segment was expected to incur compliance costs that offset any potential benefits. Across both panels of Table 3, the compliant and non-compliant portfolios generally benefited from the legislation. Interestingly, in Panel A, we find marginally significant and negative valuation effects for the non-compliant portfolio in response to event 4. Event 4 is when the Sarbanes proposal, considered to contain more stringent provisions, was passed. A comparison of valuation effects between these two portfolios shows that k4, k5, k6, and ccomb are significantly smaller for the portfolio of non-compliant firms. Taken

11

There are two systems of equations that are estimated using SUR. The first system includes the five segment portfolios, and the second system includes the compliant and non-compliant portfolios. The portfolio of all financial services firms is estimated using OLS. 12 We thank an anonymous reviewer for this suggestion. 13 Event 6, when President Bush signs the bill into law, reveals significant valuation effects for firms in the financial services industry. After ruling out the possibility of confounding effects, this result appears to reflect incremental information generated at the enactment of the law, which is consistent with the working papers of Rezaee and Jain (2003) and Li et al. (2004).

Parameter

Full sample (#201)

Adj. R2 F-value

0.7294 227.70***

P6

Small banks (#44)

þ b2p dt Rmt þ ept 0.0009 0.0004 (2.75***) (1.48) 0.9589 0.8499 (22.31***) (22.95***) 0.0008 0.0028 (0.16) (0.67) 0.0053 0.0061 (1.06) (1.46) 0.0083 0.0033 (1.72*) (0.80) 0.0068 0.0020 (1.40) (0.48) 0.0159 0.0172 (3.28***) (4.10***) 0.0162 0.0058 (3.32***) (1.38) 0.3836 0.2542 (5.72***) (4.40***)

Savings inst. (#19)

Securities firms (#16)

Insurance cos. (#68)

Compliant firms (#135)

Non-compliant firms (#66)

0.0002 (0.63) 0.7547 (15.08***) 0.0050 (0.88) 0.0055 (0.97) 0.0067 (1.18) 0.0040 (0.72) 0.0226 (4.01***) 0.0160 (2.82***) 0.3592 (4.60***)

0.0016 (3.27***) 1.9731 (31.56***) 0.0012 (0.17) 0.0150 (2.13**) 0.0077 (1.07) 0.0007 (0.10) 0.0013 (0.18) 0.0036 (0.51) 0.0891 (0.91)

0.0009 (2.82***) 0.7961 (18.39***) 0.0009 (0.18) 0.0005 (0.11) 0.0099 (2.03**) 0.0068 (1.40) 0.0185 (3.79***) 0.0148 (3.00***) 0.4989 (7.38***)

0.0008 (2.86***) 0.9280 (25.74***) 0.0014 (0.35) 0.0018 (0.44) 0.0079 (1.96**) 0.0039 (0.95) 0.0175 (4.30***) 0.0132 (3.23***) 0.3617 (6.43***)

0.0008 (3.13***) 0.9671 (28.47***) 0.0004 (0.10) 0.0022 (0.57) 0.0066 (1.73*) 0.0070 (1.84*) 0.0139 (3.61***) 0.0090 (2.33**) 0.3815 (7.19***)

0.4759 77.39***

0.7249 222.63***

0.6003 127.33***

0.7070 203.96***

0.7455 247.43***

j¼1 kjp Djt

0.6466 154.94***

0.6382 149.39***

Panel B: Rpt = b0p + b1pRmt + ccomb, pDjt + b2pdtRmt + ept b0 0.0008 0.0009 0.0004 (2.98***) (2.72***) (1.46) 0.9552 0.9759 0.8569 b1 (22.69***) (23.17***) (27.55***) ccomb 0.0052 0.0063 0.0046 (3.10***) (2.63***) (3.20***) b2 0.3531 0.3652 0.2470 (5.41***) (4.26***) (6.49***)

0.0016 0.0002 (0.62) 0.7717 (15.40***) 0.0069 (2.93***) 0.3410 (4.34***)

0.0009 (3.27***) 1.9734 (31.82***) 0.0021 (0.73) 0.0890 (0.91)

0.0008 (2.79***) 0.8150 (18.78***) 0.0060 0.0060(2.96***) 0.4788 (7.03***)

0.0008 (2.82***) 0.9429 (26.06***) 0.0058 (3.41***) 0.3458 (6.09***)

(3.10***) 0.9797 (28.80***) 0.0040 (2.49***) 0.3682 (6.90***)

Adj. R2 F-value

0.4653 196.18***

0.7246 591.34***

0.5913 325.49***

0.6997 523.66***

0.7403 640.58***

0.7227 585.67***

0.6399 399.69***

0.6328 387.53***

This table reports the abnormal returns surrounding the passage of Sarbox for portfolios of firms in the financial services industry. The parameters and t-statistics are reported from OLS estimations for the portfolio of all financial services firms, and SUR estimations for the segment portfolios. Rp is the portfolio return, Rm is the market return, Dj equals 1 for days 1 to +1 surrounding event j and 0 otherwise, dt equals 1 when Sarbox was signed into law and all subsequent days, and 0 otherwise, b0 is the intercept, b1 is the portfolioÕs beta, kj is the portfoliosÕs 3-day abnormal response to event j (Panel A), ccomb is the portfolioÕs average three-day abnormal response across all six events (Panel B), b2 is the portfolioÕs beta shift, and ep is the error term. We also report the OLS adjusted R2 and F-values. ***, **, and * indicate significance at the 1%, 5%, and 10% levels, respectively.

A. Akhigbe, A.D. Martin / Journal of Banking & Finance 30 (2006) 989–1006

Panel A: Rpt ¼ b0p þ b1p Rmt þ b0 0.0008 (3.02***) b1 0.9411 (27.24***) 0.0011 k1 (0.28) k2 0.0019 (0.49) 0.0075 k3 (1.94**) k4 0.0049 (1.26) 0.0163 k5 (4.18***) 0.0119 k6 (3.02***) b2 0.3682 (6.82***)

Large banks (#54)

1000

Table 3 Wealth effects surrounding the passage of the Sarbanes–Oxley Act of 2002 by segment

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1001

together, the results show that investors value the strong governance and disclosure of the ÔcompliantÕ firms, and the recognition that there will be greater compliance costs to offset any expected benefits for those firms that are Ônot compliant.Õ14 Table 4 reports the results of the univariate cross-sectional analyses that are conducted on the full sample of financial services firms and each subset of firms, and Table 5 reports the results of the multivariate analyses conducted on the full sample and each subset. Across both tables, these cross-sectional results demonstrate that disclosure and governance factors were important in explaining the valuation effects that resulted from the passage of Sarbox. When examining the full sample of 201 financial services firms in Table 4, all of the disclosure and governance variables are significant as hypothesized, except for insider ownership (INSIDE). It can also be seen across large banks, small banks, securities firms, insurance companies, and non-compliant firms that these disclosure and governance factors significantly influence the wealth effects. However, the variation in the valuation effects for the subsets of savings institutions and compliant firms are not explained by many of the disclosure and governance factors. For the compliant firms, the disclosure and governance factors, except as indicated by CEO involvement and institutional ownership, do not help explain the cross-sectional variation in the wealth effects. But, the stock prices of the non-compliant firms responded less favorably according to factors that indicate weaker disclosure and weaker governance. The analyses in Table 4 show that financial services firms generally experienced lower abnormal returns with lower proportion of independent audit committee (AUDIND) and if they did not meet the implied preference within Sarbox to have a financial expert on the audit committee (FINEXPT). Furthermore, it appears that firms with less footnote disclosures (FNRATIO) also had less favorable valuation effects. With the increased disclosure requirements in Sarbanes–Oxley, the market may have anticipated that those firms unaccustomed to heavy disclosure would incur greater compliance costs to implement any necessary systems and organizational structures. The analyses also show that stronger governance was rewarded. Firms with independent boards and board committees (BRDIND, NOMIND, and COMPIND) were favorably affected. The focus of Sarbox on audit committee independence may have translated to a belief that independence is value enhancing. Further evidence that the market values effective board monitoring is provided in the positive and significant BRDSTOCK and BRDCRED factors. More favorable valuation effects occurred for firms with higher proportions of the board owning stock (BRDSTOCK) and for firms with greater proportions of the board serving on other boards (BRDCRED). Thus, these results indicate that motivation and ability of the board to monitor decision-making were rewarded. Having more involved CEOs (CEOINVOLV) was viewed favorably for all subsets, except savings institutions;15 this supports our hypothesis that these CEOs can more readily comply with the Sarbox certification requirement. Greater degree of external monitoring by institutional investors (INST) was considered to be valuable. Lastly, the positive 14 We also see significant increases in market betas in the post-Sarbox period. Since we find that the variance of returns on the CRSP equally weighted market index significantly declined from 0.0100 to 0.0086, all else equal then betas would generally be expected to increase. 15 For savings institutions, CEOINVOLV is negative, which supports a counterargument that board monitoring of the firm may be less effective when the CEO has many influential roles.

1002

Table 4 Univariate regression results to explain cross-sectional variation in wealth effects for 201 financial services firms and by segment Full sample (#201)

Large banks (#54)

Small banks (#44)

Savings inst. (#19)

Securities firms (#16)

Insurance cos. (#68)

Compliant firms (#135)

Non-compliant firms (#66)

AUDIND

0.0855 (3.87***) 0.0887 (3.80***) 0.1002 (2.21**) 0.0611 (1.64*) 0.0533 (3.44***) 0.0635 (3.24***) 0.0392 (1.68*) 0.0794 (3.56***) 0.0290 (4.04***) 0.1166 (5.15***) 0.0768 (1.22) 0.0137 (3.26***)

0.1266 (4.25***) 0.1351 (5.00***) 0.1853 (2.13**) 0.0050 (0.07) 0.0953 (3.78***) 0.0945 (3.35***) 0.0893 (2.60***) 0.1619 (5.86***) 0.0247 (1.83*) 0.2154 (5.25***) 0.0527 (0.51) 0.0249 (3.66***)

0.1155 (1.89*) NA

0.0114 (0.23) 0.0106 (0.20) 0.0441 (0.47) 0.0356 (0.44) 0.0302 (0.76) 0.0291 (0.69) 0.0138 (0.26) 0.0081 (0.15) 0.0299 (2.23**) 0.0701 (1.31) 0.0361 (0.20) 0.0069 (0.57)

0.4738 (1.89*) NA

0.0774 (2.69***) 0.0900 (3.13***) 0.0872 0.0872 (1.54) 0.0052 (0.10) 0.0443 (2.12**) 0.0737 (2.65***) 0.0201 (0.68) 0.0681 (2.33**) 0.0290 (2.73***) 0.1244 (4.50***) 0.0848 (0.86) 0.0092 (1.62)

NA

0.0984 (3.00***) 0.0723 (2.78***) 0.1303 (1.85*) 0.0694 (1.07) 0.0952 (3.91***) 0.0871 (3.47***) 0.0387 (1.24) 0.0784 (2.86***) 0.0298 (2.67***) 0.1340 (3.61***) 0.0834 (0.76) 0.0195 (2.93***)

FINEXPT FNRATIO BRDIND NOMIND COMPIND BRDSTOCK BRDCRED CEOINVOLV INST INSIDE LNSIZE

0.0968 (0.82) 0.2081 (2.80***) 0.0580 (1.68*) 0.0497 (1.06) 0.0129 (0.09) 0.0804 (1.13) 0.0364 (2.69***) 0.1310 (2.22**) 0.0196 (0.13) 0.0774 (3.05***)

0.0792 (0.29) 0.0826 (0.55) 0.0115 (0.17) 0.2407 (1.69) 0.0231 (0.22) 0.0494 (0.24) 0.0618 (1.97*) 0.0911 (0.57) 0.2361 (0.99) 0.0105 (0.58)

0.1263 (1.49) 0.0534 (0.90) 0.0016 (0.03) 0.0072 0.0072 (0.31) 0.0370 (0.87) 0.0116 (0.31) 0.0409 (0.91) 0.0275 (2.99***) 0.0938 (3.17***) 0.0775 (1.05) 0.0070 (1.26)

The regressions are estimated using OLS with abnormal return, ccomb, as the dependent variable. The coefficients and t-statistics (in parentheses) are reported for each univariate regression. AUDIND is the proportion of independent audit committee members; FINEXPT is 1 if an independent financial expert is on the audit committee and 0 otherwise; FNRATIO is # footnote pages/total # pages in annual report; BRDIND is the proportion of independent board members; NOMIND is the proportion of independent nominating committee members; COMPIND is the proportion of independent compensation committee members; BRDSTOCK is the proportion of board members who own stock; BRDCRED is the proportion of board members with seats on other boards; and CEOINVOLV is # high profile roles held by CEO; INST is the proportion of institutional ownership; INSIDE is the proportion of insider ownership; LNSIZE is ln(equity market value); ***, **, and * indicate significance at the 1%, 5%, and 10% levels, respectively. NA means not applicable; there is no variation in these factors for these segments.

A. Akhigbe, A.D. Martin / Journal of Banking & Finance 30 (2006) 989–1006

Variable

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1003

relationship between firm size and abnormal returns is consistent with the perception that it is more (less) difficult and costly for smaller (larger) firms to comply with Sarbox. Generally, the results of the multivariate cross-sectional analyses reported in Table 5 confirm the results of the univariate analyses displayed in Table 4. To improve the degrees of freedom and reduce the impact of multicollinearity on the coefficients, we have constructed disclosure (DISCLOSURE), board monitoring (BMONITOR), and ownership structure (OWNERSHIP) composite measures.16 DISCLOSURE is measured as the sum of AUDIND, FINEXPT, and FNRATIO. BMONITOR is measured as the sum of BRDIND, NOMIND, COMPIND, BRDSTOCK and BRDCRED. OWNERSHIP is measured as the sum of INST and INSIDE. Even after constructing composite measures, significant correlation between these measures remains. Thus, we apply an orthogonalization procedure to reduce multicollinearity, where each factor, other than DISCLOSURE, is represented by the residual from a regression of all the remaining variables on the factor. Additionally, with five explanatory variables in a regression and only 19 and 16 observations for the savings institutions and securities firms segments, respectively, the multivariate results for these segments may not have sufficient degrees of freedom and should be interpreted with caution. The results for these two segments are reported for completeness, but our discussions and conclusions related to Table 5 do not focus on these two segments. In Table 5, we find a positive relationship between DISCLOSURE and wealth effects for the full sample of financial services firms and for the various subsets, except the subset of compliant firms. This finding is consistent with the univariate results of Table 4. The variables that comprise DISCLOSURE are significant in Table 4 for the full sample, large banks, insurance companies, and non-compliant firms. Since the small banks segment did not have any variation in the FINEXPT variable and did not show significance on the FNRATIO in the univariate analysis, it is not surprising that DISCLOSURE in Table 5 for small banks is not significant. Table 5 shows that the wealth effects are also positively related to the governance factors. The degree of monitoring by the board (BMONITOR) is significant for the full sample, large banks, and non-compliant firms. This is largely consistent with the univariate regression results in Table 4. With the group of insurance companies, it appears that once we control for disclosure and other governance factors in a multivariate framework, board monitoring is not significant. CEOINVOLV is positive and significant for the full sample, small banks, compliant firms, and non-compliant firms. For large banks, though, we find CEOINVOLV to have a negative influence on the wealth effects once we control for the other factors. OWNERSHIP is significant for the full sample and the various subsets, except the subset of non-compliant firms. Here in the multivariate framework again, for the compliant firms, we show that the disclosure and governance measures, except CEOINVOLV and OWNERSHIP, do not

16

To also improve the degrees of freedom in the multivariate analysis, we only include the firm size control variable. The decision to include firm size stems from its relatively consistent strong level of significance in the univariate analyses. It is noted that when the multivariate regressions include all the control variables, disclosure and governance factors (DISCLOSURE, BMONITOR, and CEOINVOLV) are still significant for the full sample. There are some differences in significance for the various segments, likely induced by fewer degrees of freedom.

1004

Variable

Full sample

Large banks

Small banks

Savings inst.

Securities firms

Insurance cos.

Compliant firms

Non-compliant firms

Intercept

0.0266 (0.78) 0.0507 (3.25***) 0.0333 (2.52**) 0.0426 (3.80***) 0.1290 (3.17***) 0.0095 (1.44)

0.0793 (1.86*) 0.1214 (6.23***) 0.0871 (3.18**) 0.0571 (2.16**) 0.1791 (1.87*) 0.0254 (1.93*)

0.4084 (4.11***) 0.2604 (5.55***) 0.0001 (0.01) 0.0325 (2.98***) 0.1803 (4.10***) 0.0810 (4.04***)

0.0931 (1.29) 0.0121 (0.36) 0.0348 (1.29) 0.0446 (2.92***) 0.1210 (1.78*) 0.0064 (0.58)

0.8105 (2.05*) 0.3428 (1.98*) 0.0498 (1.05) 0.0978 (2.59**) 0.1102 (0.46) 0.0205 (0.99)

0.0156 (0.48) 0.0305 (1.87*) 0.0157 (1.06) 0.0117 (0.81) 0.2168 (4.25***) 0.0155 (2.10**)

0.1354 (0.59) 0.0129 (0.13) 0.0115 (0.58) 0.0511 (3.24***) 0.1662 (3.24***) 0.0172 (1.89*)

0.0086 (0.29) 0.0296 (1.83*) 0.0430 (2.36**) 0.0397 (2.80***) 0.0743 (1.14) 0.0021 (0.23)

201 0.1717 9.38***

54 0.5102 12.25***

44 0.5533 11.90***

19 0.2020 1.91

16 0.2857 2.20

68 0.3337 7.71***

135 0.1271 4.93***

66 0.2085 4.48***

DISCLOSURE BMONITOR CEOINVOLV OWNERSHIP LNSIZE N Adj. R2 F-value

The regressions are estimated using GLM with average abnormal return, ccomb, as the dependent variable. DISCLOSURE is the sum of AUDIND, FINEXPT, and FNRATIO; BMONITOR is the sum of BRDIND, NOMIND, COMPIND, BRDSTOCK, and BRDCRED; CEOINVOLV is # of high profile roles held by the CEO; OWNERSHIP is the sum of INST and INSIDE; and LNSIZE is natural log of equity market value. ***, **, and * indicate significance at the 1%, 5%, and 10% levels, respectively.

A. Akhigbe, A.D. Martin / Journal of Banking & Finance 30 (2006) 989–1006

Table 5 Multivariate results to explain cross-sectional variation in wealth effects for 201 financial services firms and by segment

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1005

help explain the cross-sectional variation in the wealth effects. But, for the non-compliant firms, disclosure and governance measures are significant explanatory factors.17 6. Conclusions This study examines the wealth effects from the passage of the Sarbanes–Oxley Act of 2002 (Sarbox) on firms in the financial services industry. Since the Sarbox legislation aimed to reduce the opacity of financial statements, we hypothesize and find that the more opaque segments experienced net gains from its adoption. The cross-sectional importance of the Sarbox emphasis on improving the integrity of financial reporting by enhancing corporate disclosure and governance practices is also examined. We investigate whether disclosure and governance characteristics explain the variation in the wealth effects from the passage of Sarbox. Several of the significant factors are indicative of a compliance cost hypothesis. In particular, we find that financial services firms experienced less favorable effects with a less independent audit committee, without a financial expert on the audit committee, with less financial statement footnote disclosures, with less involved CEOs, and if they were smaller. The market may have viewed firms with these characteristics as likely to incur greater costs to implement any necessary systems and organizational structures to comply with Sarbox. In addition, reflecting the value of stronger governance, more favorable effects occurred for financial services firms with a greater degree of independence of the board and the board committees, when there is greater motivation and ability of board members to monitor the firm, and with a greater degree of institutional ownership. Consistent with the Sarbox focus on monitoring and control, it appears that the market finds stronger governance to be value enhancing. Lastly, we find the wealth effects of Ônon-compliantÕ firms to be significantly lower compared to the wealth effects of ÔcompliantÕ firms. For these Ônon-compliantÕ firms, the crosssectional variation in wealth effects is explained by disclosure and governance measures; weaker disclosure, weaker board monitoring, and a less involved CEO is associated with lower wealth effects. References Aharony, J., Saunders, A., Swary, I., 1988. The effects of DIDMCA on bank stockholdersÕ returns and risk. Journal of Banking and Finance 12, 317–331. Barth, J.R., Caprio, G., Levine, R., 2004. Bank regulation and supervision: What works best? Journal of Financial Intermediation 13, 205–248. Bhargava, R., Fraser, D.R., 1998. On the wealth and risk effects of commercial bank expansion into securities underwriting: An analysis of Section 20 subsidiaries. Journal of Banking and Finance 22, 447–465. Bloomfield, R.J., Wilks, T.J., 2000. Disclosure effects in the laboratory: Liquidity, depth, and the cost of capital. Accounting Review 75, 13–41. Cornett, M., Tehranian, H., 1989. Stock market reactions to the depository institutions deregulation and monetary control act of 1980. Journal of Banking and Finance 13, 81–100. Cornett, M., Tehranian, H., 1990. An examination of the impact of the Garn-St. Germain depository institutions act of 1982 on commercial banks and savings and loans. Journal of Finance 45, 95–111. 17 Comparisons of the regression coefficients in Table 5 between these two groups show the sensitivity of noncompliant firm abnormal returns to BMONITOR is significantly greater than the sensitivity of compliant firm abnormal returns.

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