Financial decisions and top management team composition

FINANCIAL DECISIONS AND TOP MANAGEMENT TEAM COMPOSITION

Conrad S. Ciccotello, Edward J . Conrad, Michael J . Fekula, and C . Terry Grant

ABSTRACT We study the relationship between financial decision making and top management team (TMT) composition using a sample of firms that choose the early adoption of the income decreasing accounting standard, SFAS No . 106 . If early adoption addresses political costs or signals future performance improvement, then the decision is one that demands a high level of accounting and finance sophistication . We observe that the TMT composition of early adopters is consistent with this expectation . Relative to a control group, TMTs of early-adopting firms are nearly twice as likely to have dominant functional backgrounds in accounting and finance . Early adopters' TMTs also tend to have newer members, suggesting a bias for action .

Advances in Accounting, Volume 17, pages 91-109 . Copyright ® 2000 by JAI Press Inc . All rights of reproduction in any form reserved . ISBN : 0-7623-0611-4 91



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C . S . CICCOTELLO, E . J . CONRAD, M. J . FEKULA, and C. T. GRANT

INTRODUCTION This study integrates theory and empirical results from research in accounting, management, strategy, and finance to examine the linkages between top management team (TMT) composition and financial decision making . We focus on a specific business decision where TMT composition may matter-the early adoption of Statement of Financial Accounting Standards (SFAS) No . 106 : Employers' Accounting for Postretirement Benefits Other than Pensions . Early adoption provides an interesting opportunity to study TMTs' financial decision making because SFAS No . 106 generally had a large negative impact on income, making early adoption seem questionable . Managers also had a four fiscal-year window (1990-1993) to adopt, giving them a great deal of flexibility to time the adoption to accomplish various motives . Our research complements prior work by Amir and Livnat (1996) and Amir and Ziv (1997) that addresses the performance rationales for early adoption of SFAS No . 106 at the firm level . We also rely on foundations built by Watts and Zimmerman (1990) on the "big bath" rationale, by Watts and Zimmerman (1978) and Zmijewski and Hagerman (1981) on political costs, and by Schipper (1989) on earnings management. This research differs from that of Amir and Livnat (1996) and Amir and Ziv (1997) in two important ways-motivation and scope . Rather than focusing on the performance of firms that adopt SFAS No . 106 early, we study the link between TMT characteristics and the early adoption decision . In addition, we examine only firms that adopt SFAS No . 106 early and make no other accounting changes in that fiscal year . Despite the restrictive sample, our firm-level performance results tend to confirm those of Amir and Livnat (1996) and Amir and Ziv (1997) . We observe several differences between the TMTs of early adopters and a firm size and industry matched control group of TMTs from firms that do not adopt early . Early adopters' TMTs have a stronger functional orientation toward accounting and finance, consistent with higher levels of expertise in these areas . Early adopters' TMTs also have newer members, relative to the control group, suggesting a bias toward action . The firm level results suggest that managers who choose to adopt SFAS No . 106 early do so to either address political costs or communicate expectations for strong future performance . Since early adoption alters the status quo, and appears to be done for sophisticated accounting and finance reasons, the findings demonstrate a link between TMT composition and financial decision making . The rest of this paper is organized as follows . The following section outlines the hypotheses . The next section describes the data . The remaining sections discuss the results, and present the conclusions and limitations .



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TOP MANAGEMENT TEAM HYPOTHESES Close scrutiny of the characteristics of TMTs may bring additional insights into the process of financial decision making . Prior research, such as Reckers (1984), demonstrates that personal and team characteristics impact decision making in an auditing context. The literature also relates managerial characteristics to decision making within the firm . For example, Strong and Meyer (1987) find evidence of managerial turnover in the year prior to the announcement of voluntary asset write-offs . The decision to adopt SFAS No . 106 early may be linked to TMT characteristics, such as tenure . Bantel and Jackson (1989) argue that TMTs with longer tenures exhibit a larger commitment to the status quo . Katz (1982) demonstrates that tenure is positively associated with a rigid attachment to established policies and practices . Greiner and Bhambri (1989) show that the arrival of a new TMT member often leads to strategic changes and new initiatives . Building on this research, we examine the characteristics of the TMTs of early adopters versus a control group comprised of TMTs of firms that do not adopt early . Early adoption is consistent with a bias toward action, and inconsistent with a high level of satisfaction with the status quo . If TMTs with longer tenures are more reluctant to engage in early adoption, then the TMTs of early adopters should have newer members than the control group . Hypothesis 1 . TMTs of early adopters have newer members than a control group of nonearly adopters . Boeker (1997) and Wiersema and Bantel (1992) argue that the heterogeneity of a TMT's tenure is an important factor in decision making . TMT heterogeneity is computed by subtracting the tenure of the member of the team who has been there the shortest amount of time from the tenure of the member who has been on the team the longest . Wider diversity in tenure increases the chances that the TMT will change past patterns and consider new practices, policies, or strategies . Less impetus for organizational change exists when TMT members' tenure is more homogeneous . To test whether the decision to adopt SFAS No . 106 early is linked to a TMT's tenure heterogeneity, we again compare this characteristic in the early adopters and control group . Hypothesis 2. TMTs of early adopters have greater tenure heterogeneity than a control group of nonearly adopters . TMT size may also impact the decision to adopt SFAS No . 106 early . Boeker (1997) suggests that larger teams can more easily develop factions that inhibit consensus on critical decisions . Larger teams also face more difficult coordination challenges because of the increasing number of notential interactions among the



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C . S. CICCOTELLO, E . J . CONRAD, M. J . FEKULA, and C . T. GRANT

members . Smaller teams may thus be more effective, as Yermack (1996) argues in the case of corporate boards of directors . In the case of SFAS No . 106, smaller TMTs may increase the chance that the early adoption decision is made. Hypothesis 3 . TMTs of early adopters have smaller team size than a control group of nonearly adopters . Prior research also indicates that a TMT's dominant functional background influences its actions . Waller, Huber, and Glick (1995) demonstrate the link between executives' functional background and their perceptions, selective attention, and judgment. Thomas, Clark, and Gioia (1993) argue that executive perceptions influence their choices and actions . Michel and Hambrick (1992) document the connection between TMTs' functional experience and firm performance . This research suggests that TMTs dominated by members with accounting and finance backgrounds focus more on these aspects of the firm's operations than teams without this orientation . As they devote more time and attention to accounting and finance, they should understand more completely the costs and benefits of relying on methods such as early adoption of accounting standards to address political costs and communicate private information . Hypothesis 4. TMTs of early adopters have more of a functional orientation toward accounting and finance than a control group of nonearly adopters .

DATA AND METHODS To screen for firms that adopt SFAS No . 106 early, we search the National Automated Accounting Research System (NAARS) database . Scanning audit reports, financial statements, and footnotes for key words such as "employee health care benefits," or "change in accounting principle," and for key numbers such as "106," produces a sample of 78 firms that adopt SFAS No . 106 early and make no other accounting changes in that same year . Eliminating firms that make multiple changes reduces the potential sample size by about two thirds . We choose this data set to provide a clean sample for the analysis of the relationship between certain early adoption motives and TMT characteristics . We exclude firms with multiple changes for several reasons . They may be using the adoption of multiple standards not for political cost or signaling purposes, but because the effects of one adoption offset the other. For example, Exxon adopted both SFAS No . 106 and SFAS No . 109 in 1992. SFAS No . 106 resulted in a reduction in net income of $800 million while SFAS No . 109 resulted in an addition to net income of $760 million . Firms may also engage in multiple adoptions with the goal of minimizing internal accounting and transactions costs associated with the changes . Table 1 lists the number of firms in the sample by fiscal year .



Top Management Team Composition Table 1 .

Notes:

95

Number of SFAS No . 106 Early Adopters

Fiscal Year

Number of Adopters

1990 1991 1992 1993

4 41 30 3

Total

78

This table shows the number of firms who adopt SFAS No . 106 in a fiscal year before that required by the FASB. For these firms, the adoption of SFAS No . 106 is the only accounting change in the given year. Fiscal year 1990 includes all firms with fiscal years ending between July 1990 and June 1991, and so on .

TMT Data We gather management team demographics from Dun and Bradstreet's Reference Book of Corporate Management using the years 1990 through 1993 . The demographics include TMT members' age, education, tenure, and dominant functional background . To define the members of the TMT, this study relies on the research of Michel and Hambrick (1992) . They suggest that the TMT consists of only positions above (but not including) the Vice President level . This definition of the TMT reduces the size of the team considerably . For each firm, we define TMT characteristics as of the year of adoption of SFAS No . 106 . TMT age is the median of the ages of the members . Education is the median of the number of years of schooling that the TMT members have (for example, "16" is a Bachelor's degree) . Organizational tenure is the median number of years that the members of the TMT have been with the firm . TMT tenure is the median number of years that the individual members have been on the TMT . Also reported is the time a TMT has been together as a team (unit tenure) . This is determined by finding the tenure of the member of the TMT who has been on the team the shortest amount of time . TMT heterogeneity is computed by subtracting the tenure of the member of the team who has been there the shortest amount of time from the tenure of the member who has been on the team the longest . TMT members' functional background is defined by categorizing the main career track they have followed throughout their employment history . This study builds on the research of Bantel and Jackson (1989), Michel and Hambrick (1992), and Murray (1989) and develops 10 categories as follows : Category 1 : Legal, Category 2 : Personnel/Labor Relations, Category 3 : Finance/Accounting, Category 4 : Management/General Business, Category 5 : Marketing/Sales/Public Relations, Category 6 : Engineering, Category 7 : Production/Operations/Manufacturing, Category 8 : Administrative, Category 9 : Research and Development, and Category 10 : Management Information Systems . A TMT's dominant functional background is obtained by categorizing the career track of each TMT mem-



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ber and observing which career track characterizes the plurality of the TMT . This plurality career track is considered the TMT's dominant functional background . We break ties by considering the functional background of the Chief Executive Officer . As an additional measure of functional background, we observe whether an absolute majority in any of the functional disciplines exists . Complete TMT demographics are available for 64 of the 78 early adopting firms . Each of the early adopter's TMTs is then matched to a TMT of a nonearly adopting firm . To control for possible bias in TMT demographics related to firm size and industry, matching firms for each early adopter are in the same two-digit SIC and within 50 percent of adoption-year sales . Wilcoxon tests are used to examine the two groups for systematic differences in characteristics . The percentages of teams having a dominant accounting and finance orientation are evaluated using a t-test for difference in proportions . Operating and Market Performance Data For the descriptive study of firms that adopt early, we develop industry benchmarks from firms listed on Compustat that are in the same two-digit Standard Industrial Classification (SIC) as the early-adopting firm . The early adopters themselves are removed from the industry benchmarks . We then compare the size and profitability of the early adopters relative to industry peers . We examine performance changes for the sample firms between the year before, the year of, and the year after the early adoption . We use the firm itself as the control for accounting performance changes since comparisons to industry performance are possible from the descriptive study discussed above . Operating income ratios are used because they represent a relatively clean measure of profitability . These ratios are free in all three years from bias created by the largest income statement impact of SFAS No . 106, expensing of the transition obligation, that is accounted for on the income statement below income from operations as the "effect of an accounting change ." The transition obligation represents the difference between the actuarial present value of future benefits attributed to employees' services rendered to the adoption date and the fair value of the plan assets . Since most plans are unfunded and most employers accrue post-retirement benefit costs for the first time, a large transition obligation generally occurs at adoption . The FASB decided to permit firms to choose either immediate expense recognition of the transition obligation or deferral and amortization . Over 90 percent of our sample firms selected immediate expense recognition . In addition to operating performance, abnormal stock returns are examined for fiscal years -2, -1, 0, and + 1, which represent the two years preceding implementation, the year of implementation, and the year after implementation, respectively . This procedure is similar to that employed by Elliott and Shaw (1988) . The return data is gathered from the Center for Research in Security Prices (CRSP)



Top Management Team Composition

97

daily returns tape . Sixty of the early adopters have no more than one daily return missing from any of the fiscal years examined . Seven firms are eliminated due to a significant amount of missing data (approximately two of the fours years studied are missing) . Eleven firms are lost since these firms are not included on the CRSP tapes . We examine abnormal security returns in the years surrounding the adoption of SFAS No . 106 . For each return observation for firm i in period t the abnormal return is calculated as the residual from a market model regression of the form :

ai + bi(Rmt) + eit rit return for firm i on day t, rit ai • intercept for firm i, bi • slope coefficient for firm i, equally-weighted New York Stock Exchange (NYSE) and American Rmt

eit

Stock Exchange (AMEX) return if the early adopter is on NYSE or AMEX . Over-the-counter (OTC) firms' returns are compared to the equally weighted OTC market return, • error term satisfying the assumptions of the standard linear regression model .

The model's parameters are estimated over the immediately preceding fiscal year using the CRSP daily returns tape . These parameters derive the abnormal returns (actual return less predicted return) for the next year . For example, a firm with a fiscal year ending December 31, 1992, would have its abnormal returns for Year-1 (the year ending December 31, 1991) calculated by a market model regression with coefficient values derived from application of the regression equation in Year-2 (the year ending December 31, 1990) . The differences between abnormal returns from one year to the next then form the basis for the analysis of changes in market performance around the adoption .

RESULTS AND DISCUSSION TMT Composition Table 2 summarizes the ages, education levels, tenures, and functional backgrounds of the TMTs of early adopters and the control group of nonadopters . The TMTs of the sample and control groups are not different in age or education level . The central tendency is for TMTs to have members in their late 50s, with education levels slightly higher than a bachelor's degree (16 years of education represents high school completion plus four years of college) . Despite the similarity in age and education, the TMTs are different in several measures of tenure . Many of these differences are consistent with H1, and suggest



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that the TMTs of early adopters have a bias for action . For example, the median TMT tenure of early adopters is significantly less than that for the control group (eight versus 11 years) . The median unit tenure (the amount of time since the arrival of the newest member of the team) is four years for the sample versus six years for the control group (p = .06) . New members have entered the TMT within three years of the 106 adoption in over 40 percent of the sample . One anecdotal example is Abbott Laboratories, where a new CFO joined the TMT the year prior to Abbott's early adoption of SFAS No . 106 . Greiner and Bhambri (1989) argue that the arrival of a new team member may bring about new initiatives . As these new policies take effect, a firm's performance outlook may improve . We subsequently test whether TMTs are timing early adoption to coincide with the beginning of an operating and market resurgence . Despite the differences in relative tenures between the control and sample TMTs, the actual tenures within the sample group are quite high . As the median organizational tenure of the early adopters' group is 20 years, and the median TMT tenure is eight years, it is difficult to classify these teams as new . How can the high absolute tenures of early adopters' TMTs be explained? Part of the explanation lies in the nature of the early adoption decision . The FASB gave firms a fixed window for adoption . This makes the early adoption timing different from firm specific decisions, such as asset write-downs, which may occur entirely at management's discretion . These decisions often virtually coincide with management changes, as Strong and Meyer (1987) observe . For early adoption, the window for decision making is exogenous to the firm . As such, there is no reason to believe that TMTs of early adopters would be new as of the early adoption date . The central tendency, however, is for them to have less tenure than a control group . The absolute tenures of early adopters suggest that the teams have had sufficient time together to be confident in their projections . These "solid" early adopting teams are surprisingly homogeneous in terms of TMT tenure . Table 2 shows that, inconsistent with H2, early adopters' TMTs tend to have less tenure heterogeneity than the control group, although the difference is not statistically significant . Boeker (1997) argues that low TMT tenure heterogeneity slows down decision making in firms . One implication is that the arrival of new members may have a particularly important decision making impact on this type of team . Moving to team size, no evidence supports H3 . Previous research such as Boeker (1997) and Yermack (1996) finds a link between team size and decision making . But the sizes of early adopters' and control group TMTs are virtually identical . Table 2 (Panel B) shows that early adopters' TMTs are almost twice as likely to have dominant functional backgrounds in accounting and finance than the TMTs of the control group (about 40 percent versus 20 percent, respectively) . This finding is consistent with H4, and significant at the .02 level . Our results are also supportive of earlier TMT research in strategy and management (Waller, Huber, and

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Top Management Team Composition Table 2. Characteristics of Top Management Teams (TMTs) of Early Adopters Compared to a Control Group Mean

Median

P value

56 .14 57 .38

56 .67 57 .00

.80

16 .75 16 .68

17.00 17.00

.69

20 .56 23 .95

20.75 23 .00

.09

12 .19 15 .35

8.00 11 .00

.01

6 .14 7 .67

4.00 6.00

.06

5 .23 5 .34

4 .50 5 .00

.89

14.34 15.77

14 .00 15 .00

.24

Panel A: Tenure and Size Variables

Characteristic : Age Early Adopters Control Group Characteristic : Education Early Adopters Control Group Characteristic : Org. Tenure Early Adopters Control Group Characteristic: TMT Tenure Early Adopters Control Group Characteristic: TMT Unit Tenure Early Adopters Control Group Characteristic : TMT Size Early Adopters Control Group Characteristic : TMT Heterogeneity Early Adopters Control Group

Panel B : Dominant Accounting and Finance Function Variables

Characteristic : Plurality

Early Adopters Control Group Characteristic : Majority Early Adopters Control Group Notes:

Proportion

P value

25/64 (39 .1%) 13/64 (20 .3%)

.02

14/64 (21 .9%) 10/64 (15 .6%)

.47

This table compares the age, education, tenure, size, and functional composition of 64 TMTs of early adopters with a firm size and industry matched group of TMTs of non-early adopters. Panel A contains tenure and team size variables, which are measured as of the year of the adoption . Education is reported as the total number of years of schooling (16 represents a four-year bachelor's degree). Organizational tenure is the median number of years that the members of the TMT have been with the firm . TMT tenure is the median number of years that the individual members have been on the TMT. Also reported is TMT unit tenure (the time since the newest team member joined the TMT). TMT size is the number of members on the team . TMT heterogeneity is computed by subtracting the tenure of the member of the team who has been there the shortest amount of time from the tenure of the member who has been on the team the longest . Sample medians are reported for the early adopters and control group . Differences in distributions are evaluated via Wilcoxon tests . Panel B has dominant functional background variables, defined as the proportion of teams with either a plurality or absolute majority of members having accounting and finance background. In all cases, the functional background of the Chief Executive Officer is used to break ties . The differences in proportions are evaluated via t-test . All p-values are based on a two-tail test .



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C . S . CICCOTELLO, E . J . CONRAD, M . J. FEKULA, and C . T . GRANT Table 3. Correlation among the Top Management Team (TMT) Tenure and Dominant Function Variables

MAGE MOT MTT UNIT SIZE HETERO FUNC Notes:

MAGE

MOT

MTT

UNIT

SIZE

HETERO

FUNC

1 .000 P= .00 0 .588 p= .00 0.644 p= .00 0 .167 p= .06 -0 .155 p= .08 0 .016 p= .86 0 .004 p= .96

1 .000 p= .00 0 .720 p= .00 0 .237 p= .01 -0 .043 p= .63 0.072 p= .42 -0 .132 p= .14

1 .000 p= .00 0.318 p= .00 -0.182 p= .04 0 .062 p= .49 -0.049 p= .58

1 .000 p= .00 -0 .368 p= .00 -0 .357 p= .00 -0 .139 p= .12

1 .000 p= .00 0.286 p= .00 0 .058 p= .52

1 .000 p= .000 -0 .006 p= .94

1 .000 p= .000

This table presents Pearson correlation coefficients for the various TMT tenure and dominant function variables. The sample of 128 firms includes 64 TMTs of SFAS No . 106 early adopters with a firm size and industry matched group of TMTs of non-early adopters . The age, organizational tenure, and team tenure for a given TMT is the median age (MAGE), organizational tenure (MOT), and team tenure (MIT) of its members in the year of adoption . TMT unit tenure (UNIT) is the time that the TMT has been together as a unit (the time since the newest team member jointed the TMT) . TMT size (SIZE) is the number of members on the team . TMT heterogeneity (HETERO) is the difference between the tenures of the longest and shortest serving members of the team . Dominant functional background (FUNC) is a dummy variable that takes a value of one if at least a plurality of members have an accounting and finance background . In all cases, the functional background of the Chief Executive Officer is used to break ties .

Glick 1995 ; Thomas, Clark, and Gioia 1993 ; Michel and Hambrick 1992) linking managerial functional background with actions and skills . Under the absolute majority definition of dominant function, the early adopters also had a higher percentage than the control group, but the difference is not statistically significant . TMTs with strong orientations towards accounting and finance are arguably more familiar with the financial operations of the firm than TMTs without such a strong orientation . This familiarity builds confidence in their financial projections . These TMTs may also be better able to gauge analyst's reactions to the information communicated by early adoption . For the TMTs of early adopters, the selective use of accounting changes is thus a convenient method of communicating their expectations about performance improvements . While the effects of TMT functional orientation and tenure provide interesting results in isolation, some multivariate analysis may give additional insights into the relationship between TMT composition and financial decision making . Table 3 shows Pearson correlation coefficients for the tenure and function variables for the 128 TMTs under study . While the positive correlation among many of the tenure variables (such as age, organization, and team tenure) is not surprising, Table



1 01

Top Management Team Composition

Table 4.

Logistic Regression of Early Adoption Decision on Top

Management Team (TMT) Tenure and Dominant Function Variables Model I Coefficient (p-value)

Model 2 Coefficient (p-value)

Model 3 Coefficient (p-value)

Model 4 Coefficient (p-value)

-1 .96 ( .04)

-1 .81 (.06) - .85 (.22)

Independent Variable Median Age of TMT Members (MAGE)

-3 .37 ( .43)

Median Organizational Tenure of the TMT Members (MOT)

- .85 ( .31)

Median Team Tenure of the TMT Members (MTT) Time Since Arrival of Newest TMT Member (UNIT)

-1 .39 ( .05)

-1 .28 ( .07)

-1 .08 ( .14)

Number of Members on TMT (SIZE)

-.78 ( .41)

-.70 ( .47)

- .97 ( .31)

TMT Tenure Heterogeneity (HETERO)

-1 .24 ( .05)

-1 .21 ( .05)

-1 .06 ( .10)

-1 .21 ( .05)

Dominant Accounting and Finance Functional Background on TMT (FUNC)

.87 ( .04)

.82 ( .05)

.90 ( .03)

.87 ( .04)

R Squared (Cox and Snell)

.10

.11

.13

.12

P-Value of Model Significance (Chi Square Test)

.02

.01

.00

.00

Notes: This table presents logistic regressions of a dummy dependent variable that takes a value of one if the firm is an early adopter of SFAS No . 106 . In the sample of 128 firms, there are 64 TMTs of SFAS No . 106 early adopters and a firm size and industry matched group of 64 TMTs of non-early adopters. The independent variables include the logarithms of each TMT's median age (MAGE), organizational tenure (MOT), and team tenure (MTT) in the year of adoption . TMT unit tenure (UNIT) is the time that the TMT has been together as a unit (the time since the newest team member joined the TMT) . TMT size (SIZE) is the number of members on the team . TMT heterogeneity (HETERO) is the difference between the tenures of the longest and shortest serving members of the team . Dominant functional background (FUNC) is a dummy variable that takes a value of one if the TMT has at least a plurality of members with a dominant background in accounting and finance .

3 shows no significant correlation between function and tenure . This suggests that both of these classes of independent variables could have power in a multivariate context. Table 4 provides the results of four logistic regressions of a dummy dependent variable that proxies for early adoption on various tenure and function independent variables. These four regression models demonstrate the robustness of the findings to changes in the patterns and characterizations of the independent variables. Consistent with H1, the team tenure variables tend to have negative and significant values . Also in line with the earlier results, early adopters' TMTs tend to be more homogeneous than the control group . The tenure heterogeneity variable



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has a negative impact on early adoption in all four regressions . This is not supportive of H2 . As argued earlier, the arrival of a new team member may be very important to inspire decisions, especially when the team is relatively homogeneous in terms of tenure . In support of this argument, each of the four regressions in Table 4 show that the time since the arrival of the newest member (unit tenure) is negatively correlated to the likelihood of early adoption . The difference is statistically significant in two of the models . Lastly, the logistic regression results confirm the univariate findings supporting H4 . The dominant function variable is positive and significant in all four models . This is again evidence of the positive association between a TMT's accounting and finance functional orientation and the likelihood of early adoption of SFAS No . 106 . Political Cost Motivation We now turn to an examination of whether early adoption is linked to sophisticated accounting and finance rationales, such as political cost reduction . Table 5 shows the industry breakdown for the early adopters in the sample . The most heavily represented are pharmaceuticals (28XX), wholesaling (51XX), and depository institutions (60XX), with 5, 6, and 5 firms out of 78, respectively . The government closely regulates two of the top three industries in the sample, pharmaceuticals and depository institutions . Sample early adopters include Abbott Laboratories, Bristol Meyers Squibb, First Boston, and Norwest . Table 6 provides descriptive financial information for the early adopters and their respective industry benchmarks (median benchmarks are used to reduce the impact of outliers) . While early adopters tend to be larger and more highly leveraged than their industry counterparts, they also have better interest coverage . Median interest coverage for the early adopters is almost three times that of the industry in the year of adoption . Profitability measures of early adopters are generally higher than those for the industry throughout the three-year period studied, especially in the year prior and the year after the accounting change . These findings are consistent with the argument that TMTs of early adopters recognize that their firms can take advantage of the flexibility of early adoption . Watts and Zimmerman (1978) argue that political costs explain why larger and more profitable firms are more likely to adopt accounting changes that reduce earnings. Zmijewski and Hagerman (1981) provide support by finding that large firms tend to favor income-deflating methods . The industry makeup of early adopters of SFAS No . 106 coupled with their relative size and profitability reveals some evidence of why their TMTs may be especially concerned with political costs . The firms are large, highly profitable, and in regulated industries . The TMTs of the early adopters recognize that their firms are potentially vulnerable to political action if they are viewed as being overly profitable .

Top Management Team Composition Table 5.

103

Standard Industrial Classifications (SICs) of Early Adopters

Two-Digit SIC 51XX 28XX 60XX 20XX 38XX 34XX 27XX 33XX 53XX 54XX 35XX

Durable Wholesales Pharmaceuticals Depository Institutions Food Products Measurement Systems Metals Printing Steel General Merchandise Food Stores Machinery

1OXX 14XX 26XX 29XX 36XX 44XX 49XX 63XX 67XX 73XX 78XX

Agriculture Mining Paper Refining Electric Equipment Water Transportation Utilities Insurance Investments Services Motion Pictures

Number of Firms

Percent of Sample

6 5 5 4 4 4 3 3 3 3 3 2 2 2 2 2 2 2

7 .7% 6 .4% 6 .4% 5 .1% 5 .1% 5 .1% 3 .8% 3 .8% 3 .8% 3 .8% 3 .8% 2 .6% 2 .6% 2 .6% 2 .6%

2 2 2 2

2 .6% 2 .6% 2.6% 2.6%

All other SICs

13

16.7%

Total :

78

100 .0%

Notes :

2 .6% 2.6% 2.6%

This table provides a breakdown of the two-digit SIC codes for the 78 firms that adopt SFAS No . 106 in a fiscal year before that required by the FASB . These firms make no other accounting changes in this same year.

Operating Performance Changes and TMT Motivations We now examine whether early adoption conveys insider information . Sophisticated TMTs could use the timing flexibility to convey their expectations for improved future performance . They may, for example, time the adoption to coincide with poor performance and execute a successful "big bath" consistent with Watts and Zimmerman (1990) . Table 7 highlights the changes in operating performance for the early adopters in the years surrounding the adoption . Table 7 (Panel A) shows evidence of a drop in operating performance from year -1 to year 0 . The change in the ratio of operating income to total assets is negative and significant at the .05 level . Table 7 (Panel B) demonstrates that both operating ratios increase significantly from the adoption year to the year after the adoption . Nearly 90 percent of the sample firms show improvement. These results are consistent with the findings of Amir and Livnat (1996) . Although we have a more restricted sample than previous



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C . S . CICCOTELLO, E . J. CONRAD, M . J. FEKULA, and C . T . GRANT Table 6.

Item :

Descriptive Financial Data for Early Adopters Firms

Industry Benchmarks

% Positive

Wilcoxon P-value

1442 .0 1451 .5 60.4 3 .9 9.1 6.5 3.3

185 .4 91 .4 25 .4 1 .7 5 .9 4 .7 2 .1

88% 88% 95% 86% 60% 60% 56%

.00 .00 .00 .00 .02 .09 .06

1450 .2 1418 .0 66 .7 4 .3 6 .8 6 .6 1 .2 2 .6

187 .6 199 .3 22.6 1 .7 5.0 4.2 2.0 2.0

82% 82% 99% 74% 65% 60% 42% 54%

.00 .00 .00 .00 .10 .05 .05 .83

1450 .9 1388 .5 65 .6 6 .3 11 .8 9 .8 3 .7

159.7 100 .5 24 .5 1 .9 5 .4 4.9 2.1

81% 87% 99% 92% 74% 77% 62%

.00 .00 .00 .00 .00 .00 .01

Panel A : Year -1 Sales (78) Assets(78) DTA (78) TIE (72) OPA (77) OPS (77) ROA (78) Panel B: Year 0 Sales (78) Assets (78) DTA (78 TIE (72) OPA (74) OPS (73) ROA (78) ROA' (78) Panel C : Year +1 Sales (69) Assets (69) DTA (69) TIE (63) OPA (67) OPS (67) ROA (69)

Notes : This table provides median descriptive data for the 78 firms that adopt SFAS No . 106 in a fiscal year before that required by the FASB . Industry benchmarks represent industry medians . For each early adopter, the industry benchmark is the median value for all Compustat listed firms (except the early adopters) in the same two-digit SIC . Year -1 is the year before the adoption . Year 0 is the year the firm adopts SFAS No . 106. Year +1 is the year after. All numbers are in millions of dollars . Debt to assets ratio (DTA) is in percentage terms . Times interest earned (TIE) is the number of times earnings before interest and taxes (operating income) covers interest expense . Return on assets (ROA), operating income to total assets (OPA), and operating income to sales (OPS) are in percentage terms . For Year 0, ROA * is what the ratio would have been if the firms had not adopted SFAS No . 106 . The number of individual comparisons made is in parenthesis after the parameter . "Percent Positive" refers to the percentage of comparisons where the firm has a larger value than the industry benchmark. P-values are measured using the Wilcoxon matched pairs signed-rank statistic for difference in distribution. All p-values are based on a two-tail test .

researchers, our findings echo their results . These findings are consistent with the assertion that sophisticated TMTs use early adoption of SFAS No . 106 to convey expectations of performance improvement to outsiders . Table 7 (Panel C) shows that operating performance in the year after the adoption is also superior to that in the year prior to adoption .



1 05

Top Management Team Composition

Table 7.

Paired Differences of Financial Data for Early Adopters : Year of Adoption versus Surrounding Years

Performance Ratio

N

Paired % Difference

%Year 0 > Year -1

Wilcoxon P-Value

72 78 78

0.0 -0.1 -0.1

54% 47% 44%

.88 .05 .13

63 67 67

2.3 4 .7 4.0

87% 90% 91%0

.00 .00 .00

63 67 67

1 .8 3 .1 2 .2

79% 79% 81%

.00 .00 .00

Panel A: Year 0 Less Year -1 Interest Coverage Oper . Income/Assets Oper . Income/Sales Panel B : Year +1 Less Year 0 Interest Coverage Oper . Income/Assets Oper . Income/Sales Panel C: Year +1 Less Year -1 Interest Coverage Oper . Income/Assets Oper . Income/Sales

Notes: This table shows the median paired differences for the early adopters in the years surrounding the

adoption . Ratio differences are in percentages. Interest coverage is the number of times that earnings before interest and taxes (operating income) covers interest expense . Year-1 is the yearbefore adoption of SFAS No. 106 . Year 0 is the year of adoption . Year +1 is the year after . "N" represents the number of comparisons . The percentage value indicates the percentage of comparisons in which the later year had the larger value. The p-values are measured using Wilcoxon statistics . All p-values are based on a two-tail test .

Subsample Analysis of Political Cost and Signaling Motivations Suggesting that early adoption can address both political cost concerns and signal future performance improvements at once is problematic . Political cost concerns suggest that the income in the year of adoption is high ; signaling suggests it is low . How can these occur at once? To address this question of differing motivations, the sample is stratified into two groups based on a rank ordering of firms' absolute operating income in the year of adoption . Operating income as a percent of sales is then examined over the three-year period surrounding adoption . Two different patterns emerge . The 15 firms with the highest absolute operating income in the adoption year experience no statistical difference in operating performance over the three-year period . The remaining 63 firms show a marked improvement in operating performance in the year after adoption . This suggests different motivations for early adoption may exist in the subsamples . Further analysis of the top 15 firms reveals a heavy concentration from regulated industries that are susceptible to political costs . They include tobacco (Philip Morris), pharmaceuticals (Bristol Meyers, Abbott Labs, Baxter International and Warner Lambert) . oil and eas (Philips Petroleum and Sun) . and insurance comna-

106

C . S . CICCOTELLO, E . J . CONRAD, M. J . FEKULA, and C . T . GRANT Table 8. Difference in Median Daily Residual from Market Model Regression Between Fiscal-Year Periods

Difference t-statistic p-value

Year -1 less Year -2

Year 0 less Year -1

-.00012 -1 .455 .146

-.00046 -2.545 .011

Year +1 less Year 0 .00058 1 .818 .069

Notes: This table reports the differences in median regression errors for 60 firms (abnormal returns) between adjacent fiscal years (subtracting earlier year from later year) resulting from the application of equally-weighted market model parameters to daily returns data . Negative numbers indicate that the preceding year contains greater values than the most current year, while positive numbers indicate that the current year contains greater numbers than the preceding year . The market model parameters employed in calculating the current year's residuals are estimated in the immediately preceding year. For example, year -1 (year 0) has the parameters of the market model calculated from the data in year -2 (year -1) . The Wilcoxon is a single-sample test of the null hypothesis that the sample medians are the same between periods . All p-values are based on a two-tail test.

vies and financial institutions (Trans America and Norwest) . These firms report an insignificant seven percent reduction in operating income in the adoption year (p value .222) followed by an insignificant 13 percent increase in operating income in the year after adoption (p value . 103) . The remaining 63 firms report an insignificant ten percent reduction in operating performance in the adoption year (p value .286) followed by a very significant 71 percent increase in operating income in the year after adoption (p value .000) . For these firms, early adoption is more consistent with a signaling motivation . Altogether, the sub-samples reveal that TMTs are adopting early for sophisticated accounting and finance reasons-the top 15 firms are arguably more concerned about political costs while the remainder of the sample appears to be signaling expected performance increases . Market Performance Changes and TMT Motivations Table 8 presents the difference in daily market residuals between fiscal years calculated separately for each of the 60 firms . The median test indicates that the abnormal returns of year 0 are significantly negative when compared with those of year -1 . The median differences test results also indicate that year +1 enjoys greater positive abnormal returns (p value of .069) in comparison with year 0 . Our results parallel those of Amir and Ziv (1997), who argue that managers use SFAS No . 106 to convey their private information to the market . Early adopters' stock market results mirror their operating performance by falling to a minimum in year 0, then rebounding in year +1 . While the wide windows used in this study



Top Management Team Composition

1 07

undermine the direct connection of early adoption and market performance, their application is similar to that of prior research such as Elliott and Shaw (1988) . As many of the firms in the sample are strong financially, it could be argued that their TMTs have no reason to signal performance improvements . But early adoption is a newsworthy event that sophisticated managers can use to their firm's advantage . Schipper (1989) asserts that when managers have flexibility in timing the adoption of standards, they have an opportunity to convey their expectations about future performance . Implying that timing flexibility has a signaling benefit means that it may also have a cost. Inaccurate or misleading signals could damage management's credibility with the markets, undermine relationships with analysts, and reduce firm value . TMTs of early adopters have the characteristics to appreciate the signaling opportunities associated with early adoption . The market performance results suggest that investors of these firms seem to interpret the early adoption as credible communication by insiders . Such credible communication reduces information asymmetry between investors and managers and creates value, even for large and currently profitable firms .

CONCLUSIONS AND LIMITATIONS This study examines the characteristics of TMTs who choose to adopt SFAS No . 106 in a year prior to that required by the FASB . We observe that SFAS No . 106 early adoption is done for sophisticated accounting and finance reasons-concerns about political costs or signaling of expected performance increases . We also find that TMTs of early adopters tend to have newer members and a stronger functional orientation toward accounting and finance than the control group . These characteristics suggest that early adopters' teams have a bias toward action as well as a high level of accounting and finance sophistication . The successful timing of the early adoption decision reinforces the notion that the tenure and functional makeup of the TMT are relevant to decision making within firms . While our results provide circumstantial support that TMTs time adoption to accomplish certain motives-namely the reduction of political costs and signaling of performance improvement, we have no direct confirmation of the actual motivation of the individual TMT members . Recognizing that we cannot directly assess motivation, we limit the sample to those firms that do not combine early adoption with any other accounting change . Despite this more restrictive sample, our firm level results do tend to echo those by Amir and Livnat (1996) and Amir and Ziv (1997) . This sample allows a cleaner test of potential management rationales, but does not eliminate the difficult problem of identifying managerial motivation . This limitation could be partially overcome by surveying team and control group members asking direct questions regarding motivation and adoption timing . Unfortu-



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C . S . CICCOTELLO, E . J . CONRAD, M . J. FEKULA, and C. T. GRANT

nately, it is not now feasible to do this since the adoption decision took place a number of years ago . Nevertheless, survey methods could be useful in future research that attempts to link financial decision making and TMT characteristics .

ACKNOWLEDGMENTS We wish to thank Philip Reckers, the editor, an anonymous associate editor, and two anonymous referees for their assistance . In addition, Thomas Bates, Sandra Chamberlain, Betty Chavis, Ken Lorek, Walton Taylor, session participants at the American Accounting Association western regional meeting, and session participants at the Financial Management Association national meeting provided constructive comments on earlier drafts . We alone are responsible for errors and omissions .

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