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Incentives and Governance in Entrepreneurial Firms*
Ellen Engel University of Chicago
Elizabeth A. Gordon Rutgers University � New Brunswick
Rachel M. Hayes University of Chicago
April, 2001
First draft: January, 2001
*We appreciate the research assistance of Bruce Bower, Donald McLaren, Raluca Mihaila, Lee-Jean Tao, and Sandy Wu and the data assistance of Taorong Jiang. We received helpful comments from Greg Miller, Karen Nelson, Scott Schaefer, Abbie Smith and workshop participants at Harvard Business School and the University of Utah Winter Accounting Conference. This research was supported by a grant from The Kauffman Center for Entrepreneurial Leadership. Engel also acknowledges research support from the FMC Faculty Research Fund and Hayes from the William Ladany Faculty Research Fund at the University of Chicago Graduate School of Business.
Incentives and Governance in Entrepreneurial Firms
ABSTRACT
This paper analyzes corporate governance decisions at firms making initial public offerings
(IPOs) of common stock between 1996 and 1999. Our objective is to examine relationships
between firms� corporate governance practices and the quality and availability of accounting-
and market-based measures of firm performance. We collect a sample of 464 companies from
the manufacturing, internet, and technology (non-internet) industries, and examine how CEO
incentives vary with industry and with the extent of venture capital influence. We first study
determinants of executives� compensation-related incentives and share ownership at the time of
the IPO, and then examine factors affecting firms� decisions over executive compensation grants
and CEO turnover subsequent to the IPO. Consistent with prior research that finds earnings are
of limited usefulness in firm valuation for internet firms, we find internet and non-internet firms
place differing importance on earnings and information in stock returns in determining post-IPO
compensation grants. We also find that firms with little or no venture capital influence display
significantly stronger association with accounting and stock performance measures than firms
with more intense monitoring by venture capitalists.
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1. Introduction
For most firms, the initial public offering (IPO) is a key event in separating ownership
from control. Pre-IPO firms tend to feature extremely high levels of inside ownership, and any
outside owners, such as venture capitalists, tend to be specialists in developing and monitoring
new ventures. Consequently, agency issues of the type considered by Berle and Means (1932)
and Jensen and Meckling (1976) are not of first-order concern in the pre-IPO period. The initial
sale of shares to the public is often the first event in a firm�s history that necessitates careful
consideration of how to mitigate owner/manager agency conflicts. As Baker and Gompers
(1999, 2000) observe, corporate governance decisions made at the time of the IPO are, therefore,
crucially important.
Recent research has emphasized the idea that corporate governance decisions should be
affected by the firm�s information environment (Bushman and Smith, 2001). If accounting- and
market-based measures of managerial performance allow owners to effectively assess how well
managers are serving their interests, then we expect governance structures to place greater
emphasis on formal, pay-for-performance contracting based on such measures. Similarly, if
managers� actions are easily observable to the firm�s owners, then direct monitoring may play a
greater role in governance. Thus, the quality of available measures of managerial performance
is a key determinant of firms� governance decisions. A developing literature now offers
considerable evidence linking compensation and governance decisions in well established firms
to properties of accounting- and market-based measures of managerial performance. Bushman,
Indjejikian and Smith (1996) and Hayes and Schaefer (2000) show that firms substitute away
from objective and towards subjective measures of managerial performance when objective
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measures are less precise, while Bushman, Chen, Engel and Smith (2000) link ownership
concentration and monitoring incentives to properties of accounting measures.
Our aim in this paper is to examine the link between governance decisions in newly
public firms and the information environment facing those firms. We offer several reasons why
addressing these issues in the IPO setting has the potential to yield new insights. First, as noted
above, firms undergoing IPOs face many crucial governance decisions; an understanding of
factors affecting such choices would further enhance our knowledge about how firms transition
from private to public ownership. Second, the IPO context may offer a sharper test of the
hypothesis that reliance on performance-based contracts can act as a substitute for direct
monitoring. As compared to more well established firms, incentives for direct monitoring in
newly public firms would appear to be especially strong due to the high levels of retained
ownership by key investors. In addition, the literature on venture capitalists (VCs) suggests that
one key role of such financiers is to monitor top management (Barry et al., 1990). If VCs have
specialized expertise and strong incentives to monitor, then one may expect VC-backed and non-
VC-backed firms to differ systematically in both the extent and nature of performance measures
used in evaluating managers.
We argue that the recent wave of so-called �new economy� IPOs offers a unique
opportunity to probe information/governance links in newly public firms. While most prior
research has used historical data to assess the quality of accounting performance measures, we
lack such historical data for newly public firms. Research on these questions in the IPO setting
therefore requires other means of assessing differences in firms� information environments. To
do this, we rely on industry-based differences in the properties of accounting measures and argue
that internet firms differ from firms in other industries along this dimension. We note that the
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sudden rise of internet-based commerce in the late 1990s was accompanied by a considerable
degree of uncertainty about the future prospects for profitability in this industry. The new
opportunities provided by electronic commerce had no analogue in business history;
consequently, there was no track record of similar firms on which to base expectations of future
growth. In addition, recent research has shown aggregate accounting-based performance
measures such as net income to be poorly associated with market performance at internet firms
(Trueman, Wong and Zhang, 2000; Hand, 2000; Demers and Lev, 2000). These factors suggest
that traditional accounting-based measures of firm performance may be of limited usefulness in
mitigating potential owner/manager agency conflicts at internet IPOs.1 Hence, we take industry
to be a proxy for information environment, and analyze how firms� use of accounting-based
measures of performance varies with industry and with the extent of direct monitoring of top
management.2
To address these issues, we collect a sample of firms making initial public offerings
between 1996 and 1999. Our data set, which we have constructed directly from firms� proxy
statements and prospectuses, consists of 464 firms drawn from three industries: general
manufacturing, technology (non-internet-based), and internet. We then attempt to determine
how differences in the information environment and the presence of direct monitoring affect
CEO incentives, both at the time of the IPO and in the post-IPO period. Although not focused on
IPO firms, related issues have been addressed by Ittner, Lambert and Larcker (2000), who
1 We do not suggest that the use of accounting measure such as earnings should be identical in settings of valuation and contracting with executives. Gjesdal (1981) shows that the ranking of information systems in valuation settings may differ from the rankings of information systems in contracting with managers. Bushman, Engel, Milliron and Smith (2000) develop a theoretical link between the use of earnings in valuation and contracting with managers with the compensation weight on earnings being an increasing function of the weight on earnings in valuation. Empirical tests of the theory reveal positive, though not perfect, correlation between the weights in the two settings. 2 We refer to the �information environment� of the firm as encompassing the �quality� of accounting measures of performance available. We recognize that information environment may have broader implications, including the disclosure environment and information dissemination by financial intermediaries. We focus on firm performance measures as available tools for contracting with managers for reward and incentive purposes.
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consider the determinants and performance consequences of equity grants in �new economy�
firms, and Anderson, Banker and Ravindran (2000), who study the use of stock options in the
information technology industry relative to other industries. Our approach departs from other
work by emphasizing the information and monitoring environments as determinants of corporate
governance decisions in IPO firms, and by examining both IPO-date and post-IPO incentives for
top managers.
We begin by analyzing determinants of executive compensation-related incentives and
share ownership at the IPO date, using methods similar to those employed by Baker and
Gompers (1999) in their study of IPO-date incentives over the 1978-87 period. We compute
CEO pay-performance sensitivity (as defined by Jensen and Murphy, 1990) and relate this
measure to firm and executive characteristics, allowing these relationships to vary across
industries. We find that internet and non-internet firms differ systematically in how executive
characteristics are related to IPO-date pay-performance sensitivity. While CEO age and longer
tenure as CEO are associated with higher CEO ownership and overall incentives for non-internet
firms, we find no such relationships for internet firms. Additionally, as in Baker and Gompers
(1999), we find lower overall CEO incentives from compensation plans and stock ownership in
place at the IPO date as VC involvement increases.
In our analysis of post-IPO compensation grants, we find that internet and non-internet
firms place differing importance on earnings and information in stock returns in determining
executive rewards. Total compensation, which includes both cash and grants of equity-based
instruments, is positively related to earnings for manufacturing firms and stock returns for
internet firms, but not vice versa. Moreover, we find that technology firms� use of accounting
information is related to cash compensation decisions only, while internet firms� use of
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information in stock returns is related to stock-based compensation only. Partitioning our sample
by venture capital influence, we find that earnings relate positively to compensation for non-VC-
backed non-internet firms, while no such relationship exists for the VC-backed non-internet
firms. Similarly, for internet firms, returns are positively related to compensation for non-VC-
backed firms, but not for the VC-backed firms. Finally, analyses of determinants of CEO
turnover in the post-IPO period reveals that the probability of CEO turnover is inversely related
to information in stock returns for manufacturing and internet firms.
In general, we take our results to be supportive of the notion that entrepreneurial firms�
initial corporate governance and executive compensation arrangements are sensitive to the
information environment facing the firm at the time of the IPO. We document significant
industry-level differences in how newly public firms address governance issues. Notable among
these differences is the variation in reliance on performance measures in determining
compensation grants. As we hypothesized, internet firms place lesser reliance on earnings as a
measure of managerial performance as compared to manufacturing and non-internet technology
firms. Further, use of these performance measures appears to vary with the extent of direct
monitoring, as measured by venture capital influence, in a manner supporting our prediction that
the presence of intense monitoring by venture capitalists affects the use of other performance
measures in determining pay.
The remainder of the paper proceeds as follows: We describe our hypotheses and
variables in section 2. We discuss our sample selection procedures and present descriptive
analyses of the data in section 3. In section 4 we examine industry-based differences in
executive compensation-related incentives and share ownership of the firm at the time of the
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IPO, and we study the determinants of compensation and turnover in the post-IPO period in
section 5. We offer conclusions in section 6.
2. Development of hypotheses and description of variables
We approach our study of CEO incentives around the IPO from two directions. First, we
examine the incentives of CEOs in place at the time of the IPO and run a series of regressions to
analyze the relationship between these incentives and various firm- and executive-level
characteristics. We then study the post-IPO relationship between firm performance and two
governance decisions: compensation grants and turnover. In the discussion to follow, we
describe our hypotheses and the variables used in our analyses.
2.1. IPO-date incentives
Our first set of analyses is designed to examine the determinants of CEO incentives in
place at the time of the IPO. Using methods similar to those used in Jensen and Murphy (1990)
and Baker and Gompers (1999) [BG], we measure incentives as the dollar change in CEO wealth
for a $1000 change in shareholder wealth (i.e., pay-performance sensitivity).
As noted earlier, our primary interest is in assessing how differences in the information
environment and the presence of direct monitoring affect CEO incentives. Using industry as a
proxy for a firm�s information environment and venture capital involvement as a proxy for direct
monitoring, we consider the differences in overall CEO incentives at the IPO date across
industries. In doing this, it is important to control for various other firm- and executive-level
characteristics that may affect CEO incentives. Models of managerial reputation or career
concerns (Gibbons and Murphy, 1992; Jensen and Meckling, 1976) offer various predictions as
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to how CEO characteristics such as age or tenure may relate to incentive compensation. Older
managers, for example, may have shorter horizons than investors, requiring greater reliance on
formal incentive contracts. Alternatively, boards of directors may be better able to evaluate
CEOs who have been in the job for a longer time, which may suggest a lesser reliance on formal
incentives and greater use of implicit arrangements than with younger, newer CEOs. Also, given
the strong role that equity ownership plays in our incentive measures, there may be a positive
relation between incentives and tenure if CEOs accumulate equity over time.
IPO-date incentives may also be affected by whether the CEO is new (i.e., it is the
executive�s first year as CEO) and whether the CEO founded the firm. The hiring of a new CEO
around the time of an IPO may be indicative of a need for certain skills and expertise useful in
managing a public company. A new CEO of an IPO firm, then, may be expected to have a larger
impact on firm value (i.e., higher marginal productivity of effort), so higher-powered incentives
may be useful. In addition, the initial compensation/ownership package provided to a new CEO
may reflect labor market conditions or the CEO�s opportunity wage. Similarly, founders may be
expected to differ markedly from non-founder CEOs. IPO-date equity incentives for founders
will be related to the founder's retained ownership, which, as suggested in Leland and Pyle
(1977), may serve as a signal of the founder�s expectations of the firm�s future profitability.
Firm characteristics such as size, growth prospects, and age are also likely to impact IPO-
date incentives for CEOs. Percentage ownership (a contributor to pay-performance sensitivity)
is well known to decrease as firm size increases, thus reducing pay-performance sensitivity
(Schaefer, 1998). Incentives may depend on growth opportunities if managers in growing firms
have greater scope for taking actions that impact firm value. Most prior literature suggests that
firms with higher book-to-market ratio, higher capital intensity (as an inverse measure of
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intangible intensity), and lower research and development (R&D) intensity are likely to have
lesser growth opportunities. BG, however, offer an alternate perspective on these measures,
suggesting they may proxy instead for the ease with which firms can raise funds using debt. If,
compared to capital-intensive firms, R&D-intensive firms have less access to debt as a financing
instrument, then these firms may have more equity held by outsiders and hence top management
will hold smaller equity stakes. Finally, if younger firms have greater growth opportunities or
face tighter cash constraints, then they may elect to place a greater reliance on equity-based
incentive mechanisms.
2.2. Post-IPO incentives
In our second set of tests, we examine how measures of firm performance are related to
grants of compensation and CEO turnover. We focus on compensation and turnover decisions
as the primary levers available to boards of directors to ensure an appropriate reward and
incentive structure for executives, and examine the effects of both market- and accounting-based
performance measures on these decisions. Prior research has found both accounting- and
market-based performance measures to be related to compensation and turnover (see, for
example, Lambert and Larcker, 1987; Murphy, 1999; and Weisbach, 1988).
Research into the use of performance measures for contracting has emphasized how the
properties of performance measures can impact the relative extent of their use in contracts
(Banker and Datar, 1989). This literature suggests that when multiple performance measures are
available, firms will substitute away from noisy or imprecise measures of managerial actions.
This insight also implies that in firms where owners engage in considerable direct monitoring of
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top management (and hence are able to obtain reasonably precise measures of managerial
performance), less reliance will be placed on objective performance measures.
As noted earlier, GAAP has been criticized for not adequately capturing the performance
of �new economy� firms. Valuation studies of internet companies support this criticism.
Trueman, Wong and Zhang (2000) do not find a significant association between net income and
market value. Hand (2000) finds a positive relation between both R&D and marketing costs and
market values, suggesting unrecorded assets. The limited usefulness of accounting in capturing
value-enhancing activities of internet firms and our earlier discussion of the uncertainties in the
internet industry suggest that, all else equal, the governance choices of internet IPOs should
reflect substitution away from accounting-based measures relative to non-internet IPOs. Thus,
we expect to observe systematic differences in the use of measures of performance between
internet and non-internet firms.
We also expect to observe differences in the use of performance measures depending on
the extent to which owners engage in direct monitoring of top management. While monitoring is
difficult to observe directly, the varying extent to which VCs hold large ownership stakes in our
sample firms offers a proxy for direct monitoring. As the recent literature on the role of VCs
documents, these financiers specialize in the formation and development of new enterprises, and
it is common for them to play a significant supervisory role (see, for example, Barry et al., 1990
and Gompers, 1995). We therefore expect these owners to have specialized expertise in
monitoring the actions of management. Hence, firms with greater VC ownership will rely more
heavily on information gathered through monitoring in assessing the performance of top
management and will substitute away from other available performance measures.
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The balance of this section describes more specifically how we expect grants of
compensation and turnover decisions to be affected by the properties of accounting measures and
the extent of direct monitoring.
2.2.1. Compensation grants
We first study annual grants of cash and equity-based compensation to CEOs. We
describe how the level of annual compensation grants in the post-IPO period differs across
sample industries. We then perform regression analyses of the determinants of annual
compensation grant levels, first allowing the effects of firm performance on compensation to
vary across industries, and then allowing effects of performance to vary with both industry and
the extent of VC ownership. As controls, we incorporate the CEO- and firm-specific variables
discussed in the previous section and further augment the analysis by adding two additional
variables, as discussed below. Our control variables here play two key roles. First, prior
research suggests these control variables are related to compensation grants to key executives.
Second, a number of our control variables, including capital intensity, R&D intensity, firm age,
and firm risk, have been shown by Baker and Gompers (1999) to be useful predictors of the
presence of VC backing. Hence, our regression estimates of the effect of VC backing on
compensation hold constant these other factors that are known to be related to VC presence.
The two additional controls incorporated in this analysis include CEO ownership and
firm risk. Greater CEO ownership may align the CEO�s incentives with the interests of
shareholders, reducing the need for additional performance-sensitive pay (Benston, 1985;
Murphy, 1985). Alternatively, high ownership can lead to entrenchment. An entrenched
executive may be able to consume more firm resources and demand higher compensation
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because the actions of the executive are less subject to market discipline (Jensen and Meckling,
1976). Anderson, Banker and Ravindran (2000) find no relation between stock ownership and
the level of CEO compensation in their investigation of compensation in the information
technology industry.
We also consider the effect of stock price volatility on CEO compensation. Recent work
by Prendergast (2000) suggests that pay-for-performance is more likely to be observed in
situations where principals do not have a strong a priori sense for what actions an agent should
be pursuing. This argument suggests that incentive pay may be more likely in cases where the
overall environment is more uncertain. If stock price volatility reflects overall uncertainty, then
incentive pay may be in greater use when volatility is high.
2.2.2. Turnover
Next, we consider the relation between firm-level performance measures and post-IPO
CEO turnover. Prior literature has documented an inverse relationship between the probability
of a management change and market and accounting performance of the firm (Coughlan and
Schmidt, 1985; Warner, Watts and Wruck, 1988; Weisbach, 1988). As with compensation
grants, we consider management turnover to be a corporate governance decision made by the
board of directors and hypothesize that the directors consider the information environment of the
firm in effecting management changes. We therefore expect to observe systematic differences
in the association of measures of performance between internet and non-internet firms in our
estimations involving determinants of CEO turnover. We also consider the impact of venture
capital involvement and the CEO-specific characteristics discussed above.
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3. Sample selection and descriptive analyses
3.1. Sample
Our sample is drawn from the set of firms whose initial public offerings took place
between May of 1996 and December of 1999. We identified our sample firms from lists of IPO
firms produced by ipomaven.com. Our primary data requirements are financial data for the firm,
and compensation and stock ownership data for the firm�s chief executive. Financial information
is taken from CRSP and Compustat. The compensation and stock ownership information is
collected from SEC filings using the SEC�s EDGAR database. These data are included in the
prospectus filed at the time of the firm�s IPO and in the proxy statements thereafter. Because
firms were required to file financial documents with the SEC electronically starting in May 1996,
we are able to obtain the IPO prospectus data from the SEC�s EDGAR database for most firms in
our initial list of IPOs.
We selected three industries, internet, manufacturing, and technology (i.e., non-internet
computer), for analysis. These three industries were those with the largest number of IPOs over
the sample period. These industries allow for an attractive research design due to expected
differences in their information environments, with internet and manufacturing firms at opposite
ends of the spectrum and technology firms displaying characteristics of both. Since internet
companies have no unique SIC code, we initially identified internet companies from a listing in
Morgan Stanley Dean Witter�s Internet Company Handbook v.2, including actively traded firms
at June 1, 2000. We further identified internet companies in our sample using listings of sample
firms in prior studies of internet companies (Demers and Lev, 2000; Hand, 2000; Trueman,
Wong and Zhang, 2000). For the remaining sample IPO companies not classified as internet-
related, we determined if the firm is internet-related by examining the list of internet firms
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produced by internet.com and by reading descriptions of sample companies in NASDAQ�s
weekly new companies report. The industry membership of other sample IPO firms is
determined using SIC codes, with non-internet technology firms having 3-digit SIC codes of
357, 367 and 737 and manufacturing firms having 3-digit SIC codes between 300 and 399
(excluding 357 and 367).
Within these three industries, we identified 545 IPOs for which CRSP and Compustat
data were available for at least some part of the sample period. We omitted ADRs and foreign
firms, as well as small businesses that were not required to file online until later in 1996, leaving
475 firms. After the removal of spinoff companies, the sample consisted of 464 firms. Missing
CRSP or Compustat data in the IPO year further reduced the sample for the regression analyses
to 433 firms in the IPO year tests.
Table 1 reports the industry composition and calendar year of the IPO transaction of our
sample firms. Our sample consists of 216 (46.6%) firms in the internet industry, 91 (19.6%) in
manufacturing and 157 (33.8%) in technology. The number of IPOs from the years 1996 to 1998
ranges from 67 to 80 per year but increases to 239 in 1999, primarily due to a surge in internet
IPOs. It is interesting to note that while the number of internet IPOs has dramatically increased
over the sample period, the number of manufacturing IPOs has declined. In our analyses
throughout the paper, data for sample IPO firms are included for all years for which data is
available from the time of their IPO through 1999. Approximately 16.0% of our sample firms
have subsequently delisted, due primarily (90%) to acquisition by another firm.
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3.2. Descriptive analyses
We begin by examining descriptive information about compensation and characteristics
of firm performance and the information environment, both at the time of the IPO and in
subsequent years. We include mean and median information about these characteristics for the
overall sample and separately for each of the three industries in Tables 2 and 3. Table 2 presents
information about CEO compensation arrangements and several CEO characteristics, including
the CEO�s ownership percentage in the firm, CEO age and CEO tenure with the firm.
Table 2 reveals that the average value of total annual compensation grants over the
sample period is quite high, with $8,641,950 granted in the IPO year and $3,597,380 granted in
the post-IPO period, on average across all firms. There are substantial differences in the average
value of total compensation grants across firms in the three industries, with average total
compensation in the post-IPO period ranging from $1,200,940 in manufacturing firms to
$7,477,600 in internet firms. While total cash compensation of CEOs in manufacturing and
technology firms is, on average, greater than total cash compensation to internet CEOs, the
average value of stock-based awards to internet CEOs causes the average value of internet CEO
total compensation to be substantially higher than that of CEOs in manufacturing and technology
firms.
Further, the mean (median) value of the stock-based component of compensation for all
firms is $8,306,340 ($521,200) and $3,177,260 ($0) in the IPO year and subsequent years,
respectively. This suggests that stock-based awards are significant in value when awarded;
however, some firms do not grant stock-based awards annually or at all. An examination of the
sample finds that three-quarters of the firms issue options at least once during the sample period.
This finding, combined with the median stock-based compensation value of zero in the post-IPO
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period, suggests that option grants are common in our sample firms but are, in some cases,
�lumpy� in nature. Table 2 also reports that CEOs of internet firms are younger and have been
in their role as CEO for a shorter time than their counterparts in manufacturing and technology
IPO firms, with the differences most prominent between internet and manufacturing firms.
Table 2 suggests there are considerable differences in the composition and level of compensation
across the industries.
Table 3 presents descriptive information about firm performance and other characteristics
of sample firms at the IPO date and in the post-IPO period. Internet firms have, on average,
substantially larger market capitalizations than manufacturing and technology, while non-internet
firms have, on average, larger levels of sales than internet firms. Striking differences exist in
both accounting and market return performance of IPO firms in the three industries. Internet
firms display lower levels of net income, on average, in the IPO year and subsequent periods
than non-internet firms, with internet firms reporting, on average, more overall losses (85.1%)
than non-internet firms. In contrast, internet firms experienced substantially higher average
market returns in the post-IPO period (121.48%) than manufacturing and technology firms
(6.02% and 54.29%, respectively). These relationships are consistent with the low associations
between aggregate accounting measures of performance and market returns of internet firms
documented in prior research and discussed earlier.
Table 3 also reveals that the average volatility of monthly market returns of non-internet
IPO firms (17.57% and 25.33%, respectively for manufacturing and technology firms) is lower
than that of internet firms (33.19%). The differences in return volatility are consistent with the
differences across industries in book-to-market ratio − the inverse of market-to-book ratio, a
proxy for growth and investment opportunities − which averages 0.160 for internet firms,
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compared to 0.499 and 0.310 for manufacturing and technology firms, respectively, in the post-
IPO period. Overall, the results of the descriptive analyses in Table 3 suggest differences exist in
life cycle and in the level of uncertainty about firm value across firms in the three industries,
validating our premise of differing information environments across firms in the sample
industries.
We also present descriptive information about sample firms by the extent of venture
capital involvement, partitioning the sample by whether the influence of venture capital is
significant, measured as equity ownership by VCs at a level of 20% or greater of the firm. Table
4 reports descriptive information by venture influence and reveals systematic differences in firm-
and CEO-related characteristics between firms with and without significant venture influence.
Venture-influenced firms are, on average, younger and are less likely to be managed by the
founder of the firm. Venture-influenced firms also display greater average market
capitalizations, lower (and quite negative) net income and lower book-to-market ratios. CEOs of
firms with more significant venture influence owned a smaller share of the firm at both the IPO
date and in subsequent years. This smaller CEO ownership percentage may reflect either a
�crowding out� of CEO ownership by VCs or the larger market capitalization of venture-
influenced firms, which would lead to a smaller ownership percentage for a given dollar value of
equity holdings by the CEO.
4. CEO incentives at the time of the IPO
In this section we discuss our research design and results of our analyses of industry-
based differences in incentives at the time of the IPO. We measure incentives as the dollar
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change in CEO wealth per $1,000 change in shareholder wealth (b).3 In computing b, we
consider three components of CEO wealth: equity ownership, option holdings, and salary. Our
measure b is computed as the sum of the ratios of the value of each incentive component to
shareholder wealth weighted by their elasticities * 1000:
soe eMV
salaryCEOeMVoptionsCEOe
MVequityCEOb *1000**000,1**000,1* ++=
where CEO equity = the value of CEO equity holdings in the firm, obtained from proxy
statement information,
CEO options = the Black-Scholes value of CEO option holdings,4
CEO salary =the present value of the CEO salary assuming a future salary level equal to
the level in the year preceding the IPO,5
MV = the market value of the firm�s common equity, and
ee, eo and es = the elasticities of the equity, option and salary components of CEO
incentives determined as described below.
As noted in BG, the elasticity of the three components with respect to shareholder wealth
differs. The elasticity of equity holdings (ee) is 1.0 by definition. That is, a one percent change
in the firm�s market value changes the CEO�s equity value by one percent. We rely on the
Black-Scholes formula to determine the elasticity of option holdings to market value (eo). A
dollar increase in market value increases option value by N(d1), also called the Black-Scholes 3 Our measure of the dollar change in CEO wealth, b, is similar to that employed by Jensen and Murphy (1990) and Baker and Gompers (2000). As in these studies, we include in CEO wealth both pay-related wealth (i.e., salary and option) and executive holdings of shares of the firm. 4 Options issued in the current year are valued using Black-Scholes according to the terms disclosed in the prospectus, with volatility measured as industry median standard deviation of monthly stock returns in the year prior to the IPO, a risk-free rate of 6% and an assumption of no dividends over the option term. The risk free rate (as measured by the 12-month treasury bill rate) over the sample period ranged from 4.2% to 6.1%, averaging 5.4%. All results are similar if option holdings are valued using a risk free rate of 5%. Any outstanding options granted in prior years are valued using the method described in Murphy (1999). This method treats outstanding options as a single grant with a remaining term of five years and an exercise price equal to the difference between the IPO date stock price and the intrinsic value (the spread between stock price and exercise price) per share. 5 As in Baker and Gompers (1999), we compute the present value of the salary incentive assuming a constant level through retirement age (which is the larger of 65 or three years older than the current age of the CEO). We discount expected salary levels at a rate of 3%. We exclude bonuses from this analysis of cash incentives because their expected transitory nature suggests they are not a permanent component of income.
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delta (∆). The elasticity of the option is calculated by converting the dollar changes to
percentage changes: e0= ∆*(Ps/Po) where Ps is the stock price and Po is the value of the option.
At the time of the IPO, we are unable to measure the elasticity of salary to shareholder wealth
(es). As in BG, we rely on results of prior studies and assume an average elasticity of 0.1.
Table 5 reports information on the CEO incentives for sample firms at the time of the
IPO. The table displays overall levels of incentives along with details by component of CEO
pay-performance sensitivity (b), including CEO equity holdings, CEO option holdings and the
present value of CEO salary. The dollar change in total CEO wealth for a $1,000 change in
shareholder wealth (i.e., b) varies from $159.98 for manufacturing firms to $201.97 for
technology firms, on average. CEO equity holdings are the largest contributor to b for firms in
all three industries, ranging from 68.5% of b for internet firms to 84.5% for manufacturing firms.
The second largest contributor of b is CEO option holdings, which are largest for internet firms
(30.6%) and smallest for manufacturing firms (14.3%). These results are also consistent with
those in Table 2, which reveals substantial differences in stock-based grants (primarily options)
across industries, with internet (manufacturing) firms displaying the highest (lowest) average
values for stock-based grants.
The levels of our measure of incentives differ from those reported in BG for their sample
of IPO firms over the period 1978-1987. Our average overall measure of b ($186.12) is lower
than the average total b in BG ($220.71). An examination of the components of b in both
settings reveals that the contribution to b from equity holdings in our sample is substantially
lower than that in BG ($138.03 vs. $211.69) while the average pay-performance sensitivity for
the option-related component of our b measure is substantially higher than in BG ($46.09 vs.
$2.84). The latter result is not surprising given the substantial increase in the use of stock
19
options in executive compensation packages in the late 1980s and 1990s. A major driver of b
from equity (b_equity) is the percentage ownership of the firm by CEOs. A comparison of
equity holdings in the two samples reveals that CEOs in our sample firms hold, on average,
13.6% of the firm�s shares while CEOs in the BG sample hold 21.2%, on average. The
difference in ownership percentages between the samples is likely driven by two factors: 1) the
number of founders, who tend to have larger share ownerships, that remain CEO at the IPO date,
with 48.91% of founders in CEO positions in our sample vs. 56% in the BG sample and 2) the
higher percentage of firms with VC involvement, since CEOs of venture-influenced firms hold,
on average, a smaller share of the firm.
Table 5 also reports that overall incentives (b) of firms with significant venture influence
are dramatically lower ($144.50) than those in firms with little or no VC involvement ($254.32).
It is interesting to note that despite lower overall incentives, the proportion of incentives from
option holdings by CEOs in venture-influenced firms is greater (36.0%) than that in firms with
little or no VC involvement (14.3%). The levels of overall incentives at the IPO date by level of
VC involvement are similar to those reported in BG for their IPO sample from 1978-87.
We next explore determinants of CEO incentives, including share ownership at the time
of the IPO. We estimate the following model of the determinants of CEO IPO date incentives:
εαααααα
αααααα
+++++++
�+�+�+++====
% VentureCEONewMVAgeFirmTARDTAPPE
FounderTenureCEOAgeCEOTechMfgIncentivesCEOj
jj
jj
j
11109876
3
15
3
14
3
13210
__ (1)
where CEO Incentives = proxy for CEO incentives, including the dollar change in total CEO wealth (b) and dollar change in components of CEO wealth (b_equity, b_options and b_salary),
Mfg (Tech) = 1 if the firm is a general manufacturing (technology) firm; 0 otherwise, j represents the industry category (1=internet, 2=manufacturing, 3=technology),
CEO Age = age of CEO at the time of the IPO,
CEO Tenure = CEO�s tenure with the firms at the time of the IPO,
20
Founder = 1 if the CEO is a founder; 0 otherwise,
PPE_TA = the ratio of property, plant and equipment to total assets for the fiscal year end preceding the IPO,
RD_TA = the ratio of research and development expenses to total assets for the fiscal year end preceding the IPO,
Firm Age = the number of years since the inception of the firm at the time of the IPO,
MV = the natural log of the market value of common equity of the firm at the end of the first day of trading,
New CEO = 1 if the CEO is new during the IPO year; 0 otherwise, and
Venture % = percentage of equity owned by venture capitalists at the time of the IPO.
The appendix further details descriptions of variables and sources for data. The model is
estimated for the overall level of CEO incentives, b, along with the components of b, including
equity holdings, stock option holdings and salary. Given that the observed variation in CEO
characteristics across our sample suggests there may be differences in the labor markets for these
industries, we allow the effects of CEO characteristics to vary across industries with industry
interactive terms for CEO age, CEO Tenure and Founder. We estimate the model for all firms
using information from the IPO date, except PPE_TA and RD_TA, which are measured at the last
day of the fiscal year preceding the IPO date.
The results of the model are presented in Table 6 and reveal differences in the determinants
of CEO incentives for internet and non-internet firms. The overall pay-performance sensitivity,
b, is increasing in CEO tenure for technology firms. The association between CEO tenure and b
appears to be driven by the equity holdings component of b (column 4). The positive association
between CEO tenure and incentives for these firms is consistent with the discussion in section
2.1 hypothesizing that increased ownership associated with longer CEO tenure increases the
alignment of CEO incentives with those of shareholders. Tenure of internet CEOs is
dramatically lower at the time of the IPO as reported in Table 2 and is not associated with CEO
incentives.
21
The overall pay-performance sensitivity of the CEO (b) is also positively associated with
founder status of CEOs in firms in all three industry groups, but is strongest for non-internet
firms. A strong positive association between founder status and the equity holdings component
of b is a driver of the link in all industries; however, this positive relation is dampened for
internet firms by a significant negative association between founder status and incentives related
to option holdings. This negative relation suggests that internet firms do not extensively use
stock options to provide incentives to founders who likely already possess significant equity
ownership of the firm.
CEO age is positively associated with overall CEO pay-performance sensitivity for
manufacturing firms, driven by the equity component of incentives. The positive association
between CEO age and stock-based incentives is consistent with our discussion in section 2.1
concerning the lower need for explicit incentives for younger CEOs. CEO age displays a
negative association with salary pay-performance sensitivity for CEOs in all industries. The
negative association with salary incentives may also be consistent with the above discussion if
firms substitute away from salary to more explicit stock-based incentives for older CEOs. VC
involvement is also associated with overall incentives, with firms with more significant VC
involvement having lower overall incentives, driven by the equity component of b. Table 6
documents that VC involvement is positively associated with incentives from option holdings.
This contrasting result is consistent with the analysis in Table 5, which documents that despite
lower overall levels of CEO incentives, the level of incentives related to option holdings is
greater in firms with greater VC involvement.
Overall, Table 6 provides evidence that internet and non-internet firms differ
systematically in several determinants of CEO incentives. Internet firms display little or no
22
association between overall incentives and CEO tenure, age and founder status, compared with
significant positive association between incentives and these factors for non-internet firms.
Further, internet firms have higher overall average incentives compared to manufacturing firms.
The lack of association with CEO tenure and CEO age and the higher average overall incentives
for internet firms may suggest that compensation-based incentives for internet firms are
determined more by labor market factors or CEOs� outside opportunities in internet firms than in
non-internet firms. This may be the case if firm-specific human capital is less important in
internet firms than other industries or the market for CEOs for internet firms is tight given the
higher number of new internet firms requiring CEOs in recent years.
5. CEO incentives in years after the IPO
In this section we focus on incentive and governance issues of sample firms in the years
immediately subsequent to the IPO. We analyze the use of performance measures in annual
compensation grants to CEOs in years after the IPO. We examine grants of total CEO
compensation and its two primary components � cash and grants of equity-based instruments.
We first analyze determinants of CEO compensation, including performance measures and CEO
and firm characteristics. We next consider the impact of direct monitoring by venture capitalists
on the use of performance measures in our sample of IPO firms. Finally, we examine factors
associated with CEO turnovers in the post-IPO period.
5.1. Economic determinants of annual grants of CEO compensation
We now examine the impact of the firm�s information environment on the relation between
CEO compensation and firm performance for the post-IPO period. We examine both aggregate
accounting and non-accounting measures of performance and hypothesize that firms with low
23
quality information from accounting measures will substitute away from accounting measures
toward other measures. We consider earnings-based measures as summary or aggregate
accounting measures of accounting performance. We proxy for a measure of value-relevant
information other than earnings using stock returns. We do not necessarily believe that stock
returns are explicitly used in contracts, but rather that contracts use other available information.
We proxy for this additional information using stock returns, which capture the value
implications of publicly available information.
We estimate the following model of the determinants of annual post-IPO grants of
compensation and its components:
εαααααααα
ααααα
αααα
+++++++++
++++�+
�+++=
=
=
MarkettoBookTARDTAPPEtStdevOwnershipCEOPolicyCashZeroCeoNewAgeFirm
AgeCEOFounderTenureCEOMVReturnsStock
ePerformancAccountingTechMfgonCompensatiCEO
jj
jj
16151413
1211109
8765
3
14
3
13210
__Re%
)log(
(2)
where CEO Compensation represents the log of total compensation (TCOMP) or one of its components, cash (TCASH) or stock-based compensation (TSTOCK),
Accounting Performance represents one of two aggregate accounting measures of performance for the fiscal year: core earnings or loss (EARN) or return (core) on assets (ROA), with core earnings measured as net income (loss) before extraordinary items, discontinued operations and special items,
Stock Returns = total annual stock return of the firm for the fiscal year,
Zero Cash Policy = 1 if the firm discloses an explicit policy not to pay cash compensation to CEO; 0 otherwise,
CEO Ownership% = the percentage of the firm�s equity owned by the CEO at the end of the fiscal year,
Stdev Ret = the standard deviation of monthly annual stock returns for the firm for the fiscal year,
Book to market = the ratio of common equity to the market value of equity at the end of the fiscal year, and
all other variables are as defined earlier and are measured as of the end of the fiscal year.
24
The appendix further details descriptions of variables and sources for data. We estimate
the model using data for all firms for all available years subsequent to the IPO date through
1999. The model is estimated for the log of total compensation (TCOMP) along with its two
key components, cash (TCASH) and stock-based compensation (TSTOCK).6 We also consider
two aggregate measures of accounting performance � core earnings, EARN, and core return on
assets, ROA.7 The model includes proxies for various CEO- and firm-specific factors discussed
in section 2 that may impact the level of annual compensation grants by firms to CEOs.8
The results of the estimations of equation (2) are presented in Table 7.9 Panel A presents
the results of the estimations involving total compensation, while Panel B includes the results
using cash compensation and stock-based grants of compensation.10 The results suggest that
total compensation for internet firms is significantly positively associated with stock returns.
This is in contrast with the results for non-internet firms, which display no association between
total compensation and stock returns. Panel B suggests that the positive association between
6 We perform a log transformation of the compensation measure before estimating the model due to skewness in the distribution resulting from a large number of firms not granting stock compensation each year. 7 We do not predict differences in the use of the two summary accounting measures of performance (EARN and ROA) by firms in the different industries, but rather include two measures because the traditionally used ROA may not capture overall firm performance similarly for the sample industries due to differences in overall asset levels across the industries (as documented in Table 3). We also obtain qualitatively similar results when all estimations in this section are conducted using �bottom-line� earnings or net income. 8 An alternative specification used in some prior studies of the pay-performance relation would be a model of changes in compensation grants as a function of changes in accounting performance. Such a model mitigates the need to consider many of the CEO- and firm-specific variables we include as potential factors impacting grants of compensation to CEOs. We use a levels specification with appropriate controls for two primary reasons: 1) we feel a levels approach is more appropriate for the analysis of stock grants, which are an important compensation component for our sample firms and 2) the levels analyses with appropriate CEO- and firm-specific controls allow for more degrees of freedom, since a change specification would result in a large reduction in the number of sample firms due to the limited timeframe of our sample. 9 Unlike the estimation of IPO-date incentives, for parsimony we do not allow CEO characteristics to vary by industry in equation (2). Results of estimations of equation (2) with industry-specific coefficients for CEO Age, Founder and CEO Tenure are similar to those in Table 7. Coefficients on CEO Age and Founder are not significant for any of the three industries. The significance of CEO Tenure in the stock compensation regression is driven by internet and technology firms. 10 Panel B reports the results of the model with the log of stock compensation as the dependent variable using White�s adjusted t-statistics due to White�s test suggesting the potential for heteroscedasticity. White�s tests for all other models do not suggest the presence of heteroscedasticity.
25
compensation and returns for internet firms is attributed to the stock-based component of
compensation. Total compensation of manufacturing firms displays a significant positive
association with earnings. Further, cash compensation of technology firms is significantly
positively linked with both earnings and ROA. In contrast, internet firms display no association
between compensation and earnings and a negative association between total compensation and
ROA.11 While we offer no conclusive explanation for this negative association with ROA, we
observe that it is consistent with the findings in recent research of a negative association between
earnings and market valuation in internet firms (e.g., Hand (2000)).
Overall, the results in Table 7 suggest systematic differences in the use of earnings-based
measures and in the information in stock returns for sample internet and non-internet IPO firms.
In particular, the use of accounting information is associated with cash compensation decisions
for non-internet sample firms, while internet firms appear to rely instead on stock market returns
in compensation decisions in granting stock-based compensation.12 The results are consistent
with our hypotheses concerning the role of the information environment in firms� governance
decisions at the time of the IPO.
The estimations of equation (2) control for factors found to be related to compensation
levels in prior research. All forms of compensation are positively associated with firm size as
measured by the natural log of the market value of equity. The CEO�s overall ownership
percentage of the firm is negatively associated with total compensation and its cash and stock-
11 Tests of equality of coefficients on earnings measures between internet and non-internet firms reject the null hypothesis in the total compensation and total cash compensation models, except for ROA in the cash model. Similar tests on stock return measures between internet and non-internet firms do not reject the null hypothesis of equality in the total compensation and stock compensation models. 12 We also consider the possibility that board of directors of internet firms find accounting information other than core earnings to be useful performance measures in determining CEO compensation grants. We re-estimate equation (2) for total compensation and its components with measures based on components of earnings, including sales, gross profit and operating income. We find similar qualitative results in these analyses with total and stock compensation grants of internet firms displaying significant association with stock returns and no association with accounting measures.
26
based component. This suggests that lower annual incentives through compensation are required
for CEOs that hold more substantial equity of the firm in their portfolio. We find that cash
compensation is positively associated with PPE_TA and that total and cash compensation is
negatively associated with RD_TA. The sign of the coefficient on R&D intensity is consistent
with the access to capital hypothesis discussed in section 2.113
Our control for whether the firm has an explicit �no cash compensation� policy for CEOs
is found to be negatively associated with total compensation, driven by the cash component of
compensation. We use ZeroCash Policy to denote cases in which firms have a stated policy of
paying no cash compensation to the CEO.14 Because these firms explicitly do not tie cash
compensation to performance, the nature of the compensation/performance relationship differs
from that of other firms in our sample. Note that we do not code all individual observations of
zero cash compensation as "zerocash" observations. Rather, we consider those observations to be
outcomes of a pay-for-performance policy unless otherwise explicitly stated.
5.2. The role of venture capital in annual grants of CEO compensation
The analyses in the prior section explore how boards of directors of newly public firms
use information in alternative performance measures in creating incentives for CEOs to enhance
the value of the firm. The analyses hold constant alternative monitoring mechanisms. It is
13 We observe that the explanatory power of the total stock compensation estimations is considerably lower than that in the estimations of the total compensation and total cash models. Recent literature on determinants of stock option granting strategies has considered several additional variables not included in our model, including the tax rate, and leverage of the firm (for example, Smith and Watts (1992) and Yermack (1995)). We find, however, that tax status (due to large cumulative losses) and leverage do not vary greatly over our sample due to the nature of IPO firms and that variation is quite related to industry class and thus these factors would proxy for industry effects rather than their intended motivation. 14 An example of a sample firm with a �no cash compensation� policy is Primix, which discloses �Lennart Mengwall, the Company's Chairman and Chief Executive Officer, currently receives no compensation in view of certain potential restrictions under the Delaware General Corporation Law." Mr. Mengwall owns approximately 55% of Primix. Results of the estimations involving cash compensation are qualitatively similar if we estimate the model without the four �zerocash� firms.
27
reasonable to expect, however, the use of performance-based incentives would be impacted by
the extent of alternative monitoring mechanisms in place. In this section, we allow the analyses
of the use of performance measures in annual CEO compensation grants to vary by the extent of
venture capital influence � an important direct monitoring mechanism for many new public
firms. Specifically, we hypothesize that greater VC involvement will be associated with lower
overall use of incentive pay and thus expect to see lower association of annual CEO
compensation grants with measures of firm performance in firms with greater VC involvement.
We partition our sample into two types of firms � those with significant VC influence and
those with little or no VC involvement. We classify firms with significant venture influence as
those with equity ownership by VCs at a level greater than or equal to 20% of the firm. At this
level of ownership, VCs generally have significant representation on the board of directors and
thus, a strong ability and incentive to influence key decisions of the firm and engage in direct
monitoring of management.15 We separately estimate equation (2) for total compensation and
its cash and stock-based components for the two types of firms.
Table 8 reveals that the use of information in accounting and stock-based performance
measures differs between firms with and without significant VC involvement.16 The results for
firms with little or no VC involvement are consistent with those documented in section 5.1, with
compensation grants of non-internet firms displaying significant association with EARN while 15 Use of a cut-off of 20% equity ownership to classify firms with significant venture involvement is consistent the the rule-of-thumb cutoff employed in accounting standards under SFAS No 94 and APB Opinion No. 18 to determine �significant influence� for equity investments by firms. As with corporate equity investments, �significant influence� by venture capitalists can occur at levels of ownership below 20%. We test the sensitivity of our results to the chosen cut-off by replicating the analyses in this section using a cut-off of 10% equity ownership to determine significant venture capital involvement and obtain qualitatively similar results. 16 Table 8 reports estimates for intercept and performance measure coefficients. Coefficients on other variables in equation 2 are not tabulated because their significance for both venture and non-venture firms is generally consistent with those in Table 7. Coefficients on other variables do not display significant difference between venture and non-venture involvement except for RD_TA and Zero Cash Policy which display stronger negative association with compensation grants of non-venture firms. Also, Table 8 reports estimations using EARN only. Results with the accounting measure, ROA, are qualitatively similar with respect to the significance of the differences between venture and non-venture firms.
28
grants of internet firms instead display stronger association with information in stock returns.
Total and component compensation grants of firms with greater VC involvement are not
significantly associated with accounting or stock performance measures. Tests of the equality of
coefficients on performance measures across the venture capital partition reveal that
compensation grants of firms with little or no venture backing display significantly greater
association with accounting and stock return measures of performance than do grants of firms
with venture influence. Further, tests of equality of coefficients on earnings and stock return
measures between internet and non-internet firms reject the null hypothesis of equality within the
non-venture-influenced group while there are no significant differences in earnings and returns
coefficients across industries in the venture-influenced group. Overall, the results are consistent
with our hypothesis that greater levels of direct monitoring by VCs decreases the need to use
costly performance-based incentives in compensation. Further, in settings where direct
monitoring is lower and performance-based incentives are employed, use of performance
measures varies with proxies for the information environment of the firm.
The lack of significant association of compensation grants in venture-influenced firms
with the performance measures in our tests suggests not only that these boards of directors do not
base compensation on information in current accounting and market performance, but also that
CEO compensation is not based on information that is correlated with these measures. One
possible explanation for this finding is that due to closer involvement and expertise, VCs are able
to base compensation grants on information about managerial actions that is not reflected in
current period performance measures. The differing relationships between R&D intensity and
compensation (see footnote 16) across the venture capital partition may be suggestive of this
notion; increased R&D intensity has a significantly negative effect on compensation for the non-
29
venture-influenced firms, but not for venture-influenced firms, despite the finding that R&D
intensity is comparable for the two groups.17 The observed lack of association between
compensation and current performance may be a result of VCs� ability to monitor and reward
actions that have long-term implications.
5.3. Decisions involving CEO turnover
We next examine determinants of CEO turnover in sample firms in the periods
subsequent to the IPO. We estimate the following logit regression to examine the probability of
a CEO change:
εγγγγ
γγγγ
γγγγ
+++++
++++
+++=���
���
−
�
�
=−
=−
%%
)(1)(ln
111098
765
3
114
3
113210
VentureMVOwnershipCEOAgeFirm
AgeCEOFounderTenureCEOReturnsStock
ePerformancAccountingTechMfgchangeCEOP
changeCEOP
jtj
jtj
(3)
where the dependent variable is equal to 1 if a CEO change occurs during the fiscal year and zero
otherwise.18 Accounting Performance and Stock Returns are as defined earlier and are measured
for the preceding year. All other variables are as previously defined. Since we examine
performance for the preceding year for all observations, we include in our estimations all sample
firms for which data are available for two consecutive years.
Table 9 includes the results of the logit estimations of equation (3) using both EARNt-1
and ROAt-1 as measures of accounting performance in the prior year. The results show
significant negative association between CEO changes and prior year stock returns of internet
17 Alternatively, the negative coefficient on R&D intensity in non-venture-influenced firms may reflect the access to capital hypothesis discussed earlier. 18 Note that our turnover measure does not distinguish between performance-related turnover and other forms of turnover (such as retirement or accepting a preferred position in another firm). As prior work (Warner, Watts, and Wruck, 1988) has found the strongest turnover link between performance and forced departures, we expect the use of our turnover measure to weaken the power of our tests.
30
and manufacturing firms, but no association between turnover probability and prior year stock
returns of technology firms. We find that prior accounting performance (EARN and ROA) is not
linked with CEO changes in firms in any of the three industries. These results largely contrast
with those of prior large sample analyses of the relation between CEO turnover probabilities and
summary measures of firm performance, which have documented that the probability of turnover
increases with poor performance. One conjecture consistent with our finding that prior
performance is more significantly related to turnover probability for manufacturing firms than
for technology-related firms is that the business environment of the technology-oriented IPO
firms in our sample differs from that of the broader sample of firms included in prior analyses �
sample internet and technology firms are operating in environments with rapid paces of change
in product and market factors. This may suggest that more immediate performance information
or non-financial measures that capture firms� growth prospects are used by boards of directors in
making CEO turnover decisions.
Standard outlier analyses techniques reveal the presence of a single outlier observation.
Removal of the outlier does not greatly impact the magnitude or significance of the performance
measure coefficients; however, coefficients for firm age (Firmage) and venture capital
ownership percentage (Venture %) become negatively significant. This result on VC
involvement complements recent work by Hellman and Puri (2000) documenting that VC
involvement is positively associated with turnover of founding CEOs for a sample of non-public
technology firms. They conjecture that the relation is due to the professionalization of
management of start-up firms by VCs. The negative coefficient on Venture % in our study
suggests that more VC involvement is less likely to lead to CEO turnover in the post-IPO period
31
perhaps because VCs are closely involved in selecting IPO-date CEOs and, thus, bring in high
quality CEOs at or just prior to the IPO.19
6. Conclusion
In this paper, we present evidence on the relationship between corporate governance
practices and the information and monitoring environments of firms undertaking initial public
offerings of common stock. Governance issues are critical to the firm at the time of the IPO as
many firms establish a formal separation of ownership and control for the first time. We begin
with the assertion that entrepreneurial, particularly so-called �new economy� firms faced much
more uncertain prospects than firms in other, more well established industries. We exploit this
notion by using industry to proxy for firms� information environment, which allows us to probe
information/governance links in the IPO setting. Focusing on a key governance mechanism,
executive incentives, we examine firms� corporate governance and executive compensation
practices at the time of the IPO and in the period just after the IPO.
Our main results concern the relationships between financial performance measures and
annual top executive pay. We find accounting-based measures to be positively related to pay for
non-internet executives, and stock returns to be positively related to pay for internet executives,
but not vice versa. Moreover, the pay/accounting-measure relationship for non-internet
executives appears to be driven by cash compensation, while the pay/stock return relationship for
internet CEOs seems to result from grants of stock-based instruments. We take this finding to be
19 Examination of the data reveals that a small percentage of sample firms in each industry with CEO turnover involve firms with significant venture capital influence. This is not surprising given the negative coefficient on venture capital percentage ownership discussed above. As a result, we do not estimate a specification of the CEO turnover model that allows the use of performance measures in turnover decisions to vary by the extent of venture capital consistent with our analysis in section 2 due to concerns about the power of the tests.
32
supportive of the notion that firms� compensation practices reflect substitution away from
performance measures that are less precise measures of managerial value creation.
We also conduct analyses that examine the association of CEO compensation grants with
of accounting and market measures after considering the impact of venture capital influence � an
important direct monitoring mechanism in our sample of IPO firms. We hypothesize that greater
venture capital involvement mitigates the need for formal pay-for-performance contracting.
Results of analyses that partition the compensation grant model according to venture capital
influence support the hypothesis by documenting that compensation grants of IPO firms with
little or no venture influence display significantly more association with accounting
(manufacturing and technology firms) and stock return (internet firms) measures of performance.
Our analyses focus on the incentives provided to CEOs as a corporate governance
decision facing firms recently undergoing an IPO. It is likely that other governance decisions,
including board of director composition and incentives, are similarly impacted by the
information environment of the firm. In future work, we intend to examine the relationship
between information environments and other governance mechanisms across our sample
industries.
33
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34
Financial Accounting Standards Board. Statement of Financial Accounting Standard No. 94. 1987, Consolidation of All Majority-Owned Subsidiaries. Gibbons, R. and K. Murphy, 1992, Optimal incentive contracts in the presence of career concerns: theory and evidence, Journal of Political Economy 100, 478-505. Gjesdal, F., 1981, Accounting for Stewardship, Journal of Accounting Research 19, 208-231. Gompers, P., 1995, Optimal investment, monitoring, and the staging of venture capital, Journal of Finance 50, 1461-1489. Hand, J. R. M., 2000, Profits, losses and the non-linear pricing of internet stocks, University of North Carolina working paper. Hayes, R.M., and S. Schaefer, 2000, Implicit contracts and the explanatory power of top executive compensation for future performance, RAND Journal of Economics 31, 273-293. Hellman, T. and Puri, M., 2000, Venture capital and the professionalization of start-up firms: empirical evidence, Stanford University working paper. Ittner, C.D., R.A. Lambert and D.F. Larcker, 2000, The structure and performance consequences of equity grants in new economy firms, University of Pennsylvania working paper. Jensen, M. and W. Meckling, 1976, Theory of the firm: managerial behavior, agency costs and ownership structure, Journal of Financial Economics 3, 305-360. Jensen, M. and K, Murphy, 1990, Performance pay and top management incentives, Journal of Political Economy 98, 225-264. Lambert, R. and D. Larcker, 1987, An analysis of the use of accounting and market measures of performance in executive compensation contracts, Journal of Accounting Research 25, 85-129. Leland, H. E. and D. H. Pyle, 1977, Informational asymmetries, financial structure, and financial intermediation, Journal of Finance 32, 371-387. Morgan Stanley Dean Witter�s Internet Company Handbook v.2, Morgan Stanley Dean Witter and Co. 2000. Murphy, K., 1985, Corporate performance and managerial remuneration: an empirical analysis, Journal of Accounting and Economics 17, 59-76. Murphy, K., 1999, Executive compensation, Handbook of Labor Economics, 3, Orley Ashenfelter and David Card, eds. Prendergast, C., 2000, The tenuous tradeoff of risk and incentives, University of Chicago working paper.
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Schaefer, S. 1998, The dependence of pay-performance sensitivity on the size of the firm, Review of Economics and Statistics 80, 436-443. Smith, C. and R. Watts, 1992, The investment opportunity set and corporate financing, dividends and compensation policies, Journal of Financial Economics 32, 263-292. Trueman, B, M. H. F. Wong and X. J. Zhang, 2000, The eyeballs have it: searching for the value in internet stocks, Forthcoming. Journal of Accounting Research. Warner, J, R.L. Watts and K.H. Wruck, 1988, Stock prices and top management changes, Journal of Financial Economics 20, 461-492. Weisbach, M.S., 1988, Outside directors and CEO turnover, Journal of Financial Economics 20, 431-460. Yermack, D., 1995, Do corporations award CEO stock options effectively?, Journal of Financial Economics 39, 237-269.
36
Appendix Description of variables and sources of data
Variable Description and source information Compensation and components: Salary (Bonus)
Annual salary (bonus) for the fiscal year obtained from annual proxy statement.
Total Cash
Sum of annual cash compensation: Salary + Bonus + Other Annual Cash; Compensation for the fiscal year obtained from annual proxy statement. The log of total cash compensation is used in the estimations of equation (2).
Stock-based grants Value of stock-based grants (stock options and restricted stock) during the fiscal year. Value of stock options on the date of the grant were determined using Black-Scholes option pricing model where exercise price and option term are obtained from the proxy statement or prospectus, stock price at the time of grant was obtained from the CRSP daily stock price file, volatility is measured as the industry median standard deviation of monthly stock returns in the year prior to the grant, risk free rate = 6% and dividends are assumed to be zero over the option term. Value of restricted stock is obtained directly from the proxy statement or prospectus. The log of total stock-based compensation is used in the estimations of equation (2).
Total Compensation Sum of Total Cash and Stock-based grants. The log of total compensation is used in the estimations of equation (2).
CEO Characteristics: CEO ownership percentage
Percentage of shares of the firm owned by the CEO at the time of the IPO or the end of the fiscal year; obtained from prospectus or annual proxy statement, if ownership percentage is disclosed as being less than 1%, we directly computed the percentage as the number of shares owned bythe CEO from the prospectus or proxy divided by the total number of shares outstanding from CRSP.
CEO Age Age of CEO at the time of the IPO or the end of the fiscal year, obtained from prospectus or annual proxy statements
CEO Tenure Number of years that CEO has been in his/her role as CEO of the firm at the time of the IPO or the end of the fiscal year, obtained from prospectus or annual proxy statement
New CEO Dummy variable = 1 if the CEO is new during the fiscal year and 0 otherwise
Founder Dummy variable = 1 if the CEO is the founder of the firm and 0 otherwise
Appendix continued on next page.
37
Appendix (cont�d) Description of variables and sources of data
Variable Description and source information Firm and performance characteristics Market value of equity Market capitalization of the firm; natural log of MV is used in the
estimations of equations (1) and (2) ▪ At time of IPO = closing price at the end of the first day of trading *
number of shares outstanding at the end of the first day of trading; obtained from CRSP daily stock files
▪ Years subsequent to IPO = fiscal year end closing price * number of shares outstanding;
Earnings Core earnings (loss) for the fiscal year computed as net income (loss)
before extraordinary items, discontinued operations and special items; Return on assets Core earnings (loss) / total assets Stock returns Sum of monthly returns for the fiscal year obtained from CRSP monthly
stock files Stdev Ret Standard deviation of monthly returns for the fiscal year PPE_TA (Net property, plant and equipment) / (total end of year assets)
R&D_TA (Research and development expense) / (total end of year assets)
Book-to-Market ratio (Book value of common equity)/(Market value of equity)
Firm Age Number of years since inception of the firm at the time of the IPO or the end of the fiscal year, obtained from prospectus or proxy statement
Venture influence Dummy variable = 1 if venture capital equity ownership of the firm >20% and 0 otherwise, obtained from prospectus or proxy statement
Venture % % of equity owned by venture capital investors at the time of the IPO or inthe year subsequent to the IPO, obtained from prospectus
Pay-performance sensitivity measures: b_salary CEO salary/(Market value of equity)*1000*es where
- CEO salary = the present value of the CEO salary assuming a future salary level equal to the level in the year preceding he IPO and - es =0.10 by assumption
b_options CEO options/(Market value of equity)*1000*eo where - CEO options are the Black-Scholes value of CEO options holdings (see footnote 4) and - eo =Black Scholes delta*(Stock Price/Option Value)
b_equity CEO equity/(Market value of equity)*1000*es where - CEO equity is the value of CEO equity holdings in the firm and - es =1 by definition
b (overall) b_salary + b_options + b_equity All financial data for the firm was obtained from Compustat unless otherwise noted.
38
Table 1
Descriptive statistics of sample composition by calendar year of IPO
Sample by year of IPO and industry
All firms Internet Manufacturing Technology
IPO Year # of firms % of total # of firms % of total # of firms % of total # of firms % of total 1996 78 16.8% 9 4.2% 33 36.2% 36 22.9% 1997 80 17.2% 11 5.1% 34 37.3% 35 22.3% 1998 67 14.5% 23 10.6% 10 11.1% 34 21.7% 1999 239 51.5% 173 80.1% 14 15.4% 52 33.1% Total 464 216 91 157 % of total 46.6% 19.6% 33.8%
39
Table 2
Descriptive statistics of compensation information and CEO characteristics of IPO firms by industry
Means (medians) - $ in thousands All firms Internet firms Manufacturing firms Technology firms
IPO year Post-IPO
period
IPO year Post-IPO
period
IPO year Post-IPO
period
IPO year Post-IPO
period Salary
184.88 173.75
240.00 219.18
150.64 151.56
203.89 200.00
244.33 194.76
274.48 241.72
197.53 186.06
241.69 219.15
Bonus
110.09 30.00
122.76 53.33
49.67 18.38
80.12 50.00
272.96 50.00
167.83 60.00
98.82 50.00
121.45 52.28
Total Cash
321.97 220.75
383.05 285.00
209.75 183.25
305.04 253.19
549.29 275.02
454.17 322.59
344.61 240.63
389.28 283.79
Stock-based grants 8,306.34 521.20
3,177.26 0
14,380.16 760.18
7,168.31 0
1,269.49 255.01
679.76 71.36
4,287.82 542.32
1,992.39 0
Total Compensation 8,641.95 903.66
3,597.38 485.54
14,589.56 928.09
7,477.60 450.00
1,838.59 733.97
1,200.94 520.00
4,656.50 969.36
2,421.35 459.79
CEO ownership percentage
13.60% 6.90
11.46% 4.90
12.45% 7.70
10.39% 5.60
13.20% 3.90
9.34% 3.20
15.43% 8.25
13.89% 6.10
CEO age 45.38 years 45
48.06 years 47
42.48 years 42
44.36 years 44
51.54 years 52
52.67 years 53
45.80 years 46
47.39 years 47
CEO tenure 3.84 years 2.58
5.21years 3.59
2.77 years 2.25
3.43 years 3.08
4.82 years 3.00
5.90 years 3.59
4.75 years 3.16
6.07 years 4.46
Founder 48.91% 38.88% 55.14% 41.8% 30.34% 24.58% 50.96% 47.47%Firm Age 7.91 years
4.25 10.95 years
6.793.91 years
3.125.03 years
4.1715.25 years
7.00 16.51 years
8.889.15 years
6.7511.29 years
9.59New CEO 19.40% 12.63% 26.39% 13.12% 15.39% 15.83% 12.10% 9.8%# of observations 464 800 216 244 91 240 157 316
See appendix for description of variables.
40
Table 3 Descriptive statistics of firm performance and other firm characteristics of IPO firms by industry
Means (medians) - $ in thousands, except per share amounts. All firms Internet firms Manufacturing firms Technology firms
IPO year Post-IPO
period
IPO year Post-IPO
period
IPO year Post-IPO
period
IPO year Post-IPO
period Market value of equity 463,007
168,9111,133,160
270,620665,134 214,500
2,504,490 847,838
233,811 128,650
291,130 115,463
332,497 157,531
724,000 226,770
Total assets 67,990 18,975
195,493 73,302
32,764 14,919
244,596 94,218
185, 129 47,995
242,169 74,978
48,306 18,918
122,493 65,232
Sales 70,172 17,443
134,374 46,781
15,531 8,453
54,273 27,726
213,146 58,689
243,500 72,503
64,410 26,788
116,813 56,527
Net income (loss) -4,925.43 -3,862.00
-7,853.40 -2,071.00
-12,047.3 -8,443.00
-36,769.5 -17,342.00
3,601.7 1,071.00
5,134.90 1,599.50
-252.50 314.00
4,710.40 2,834.00
Return on assets -50.08% -24.00
-11.98% -2.62
-86.69% -49.49
-23.65% -18.80
-24.95% 3.32
-14.01% 1.14
-14.79 4.45
-1.47% 4.32
% of firms with net loss 66.15 53.73% 91.43% 85.12% 42.86% 45.34% 45.45% 35.78%Annual market return N/A 57.93%
6.55N/A 121.48%
41.09 N/A 6.02%
-12.50%N/A 54.29%
4.76Std. dev. of returns N/A 25.30%
22.07N/A 33.19%
28.57 N/A 17.57%
16.75N/A 25.33
22.61PPE_TA 18.66%
12.6613.68%
8.6018.60%
12.638.55%
6.10 22.88%
17.5522.04%
17.0916.27%
12.2211.34%
8.25R&D_TA 21.81%
14.9311.41%
7.2121.89%
13.748.19%
4.92 14.48%
3.2112.23%
3.4625.94%
21.6413.23%
11.50Book-to-Market ratio N/A 0.321
0.204N/A 0.160
0.096 N/A 0.499
0.373N/A 0.310
0.210Venture % 31.60%
29.7022.35%
19.7034.18%
33.6525.81%
25.30 34.51%
26.3025.28%
19.3026.36%
21.7017.45%
12.40Venture-influenced 61.21% 36.78% 68.98% 50.82% 54.95% 36.25% 54.14% 25.32%# of obs. 464 800 216 244 91 240 157 316
See appendix for description of variables.
41
Table 4 Descriptive statistics of firm performance and other firm characteristics of IPO firms
by extent of venture capital involvement Means (medians) - $ in thousands, except per share amounts.
Non-venture-influenced Venture-influenced
IPO year Post-IPO
period
IPO year Post-IPO
period Market value of equity 373,123
146,838947,890 197,843
519,637 180, 750
1,458,210 411,485
Total assets 89, 024 19,995
206,733 68,103
54, 807 17,446
176,008 80,644
Sales 100, 835 25,008
144,318 55,202
50,994 13,442
117,093 32,984
Net income (loss) 1,058.86 160.00
-3,223.50 1,206.00
-8,665.61 -5,917.50
-15,852.00 -8,888.50
Return on assets -51.23% -3.09
-7.95% 1.75
-49.37% -34.58
-17.47% -11.29%
% of firms with net loss 49.71% 46.11% 76.43% 66.90%Annual market return N/A 58.20%
4.20N/A 57.45%
10.44Std. dev. of returns N/A 24.14%
21.21N/A 27.42%
23.96PPE_TA 19.94%
13.1314.88%
9.7117.86%
12.49 11.62%
7.16%R&D_TA 20.32%
11.1611.55%
7.7222.75%
16.98 11.17%
6.85Book-to-Market ratio
N/A .360 0.246
N/A .253 0.139
Firm Age 9.33 years 5.29
12.16 years 8.59
7.00 years 4.00
8.83 years 5.17
Founder 54.49% 41.06% 45.39% 35.05%CEO ownership percentage
20.98% 15.50
14.43% 5.70
9.00% 5.30
6.31% 4.30
CEO age 46.32 years 46
48.55 years 48
44.79 years 44
47.19 years 46
CEO tenure 4.78 years 2.92
6.08 years 4.00
3.25 years 2.42
3.70 years 3.09
New CEO 16.11% 13.16% 21.48% 11.68%# of observations 180 509 284 291
See appendix for description of variables.
42
Table 5 Summary of measures of average CEO incentives at the time of initial public offering
Dollar change in CEO wealth (b) % of total
equity
Elasticity*1000Contribution
to b % of mean overall b
All IPO sample firms: CEO equity holdings 13.80% 1000.0 $138.03 74.2 CEO options holdings 3.58 2131.05 46.09 24.7 CEO salary 2.00 100.0 2.00 1.1 Total incentives 19.38 186.12
By industry: Internet firms CEO equity holdings 12.70 1000.0 127.03 68.5 CEO options holdings 4.57 1840.02 56.74 30.6 CEO salary 1.75 100.0 1.75 0.9 Total incentives 19.02 185.52
Manufacturing firms CEO equity holdings 13.51 1000.0 135.14 84.5 CEO options holdings 1.70 2199.95 22.82 14.3 CEO salary 2.02 100.0 2.02 1.2 Total incentives 17.23 159.98
Technology firms CEO equity holdings 15.43 1000.0 154.27 76.4 CEO options holdings 3.35 2476.84 45.37 22.5 CEO salary 2.32 100.0 2.33 1.1 Total incentives 21.10 201.97 By venture influence: Non-venture-influenced CEO equity holdings 21.57 1000.0 215.72 84.8 CEO options holdings 2.74 1606.45 36.41 14.3 CEO salary 2.20 100.0 2.19 0.9 Total incentives 26.51 254.32 Venture-influenced CEO equity holdings 9.06 1000.0 90.62 62.7 CEO options holdings 4.09 2451.22 52.00 36.0 CEO salary 1.88 100.0 1.88 1.3 Total incentives 15.03 144.5
See appendix for description of variables.
43
Table 6 Determinants of executive incentives at time of IPO
Dollar change in CEO wealth (b)
Total
Salary Option
holdings Equity
ownership Intercept 492.89
(3.29)a30.28
(17.47)a403.95 (4.88)a
58.66 (0.48)
Manufacturing -397.61 (-2.65)a
0.02 (0.01)
-77.62 (-0.93)
-320.02 (-2.61)a
Technology 33.39 (0.31)
0.67 (0.13)
-57.40 (-0.97)
90.62 (1.03)
CEO Tenure: Internet 1.14
(0.20)-0.02
(-0.30)-0.39
(-0.12) 1.55
(0.33) Manufacturing 1.89
(0.48)0.02
(0.32)0.16
(0.07) 1.72
(0.54) Technology 9.57
(2.92)a-0.03
(-0.72)-2.17
(-1.20) 11.77
(4.39)a
Founder: Internet 44.78
(1.73)c -0.24
(-0.79)-58.15
(-4.06)a 103.16
(4.88)a
Manufacturing 116.56 (2.77)a
0.45 (0.93)
1.86 (0.08)
114.24 (3.33)a
Technology 82.76 (2.79)a
-0.19 (-0.55)
7.85 (0.48)
75.10 (3.10)a
CEO Age: Internet 0.72
(0.48)-0.04
(-2.32)b-0.03
(-0.03) 0.79
(0.65) Manufacturing 6.94
(2.67)a -0.05
(-1.81)c 0.00
(0.00) 7.00
(3.29)a
Technology -1.39 (-0.81)
-0.04 (-2.18)b
0.35 (0.37)
-1.69 (-1.20)
PPE_TA 16.06 (0.33)
-1.22 (-2.17)b
18.06 (0.67)
-0.78 (-0.02)
RD_TA -44.31 (-1.50)
-0.51 (-1.47)
-10.83 (-0.66)
-32.97 (-1.36)
Firm Age 0.45 (0.59)
0.01 (1.26)
-0.16 (-0.39)
0.60 (0.97)
Market value (log) -15.96 (-2.39) a
-1.35 (-17.51)a
-16.81 (-4.56)a
2.19 (0.40)
New CEO 8.63 (0.38)
-0.67 (-2.53)a
2.28 (0.18)
7.02 (0.38)
Venture %
-153.76 (-5.24)a
0.02 (0.06)
33.71 (2.08)b
-187.49 (-7.83)a
Adjusted R2 .19 .45 .08 .32No. of obs. 433 433 433 433
See appendix for description of variables. t-statistics in parentheses. a,b, and c denote significant at the 1%, 5% and 10% levels, respectively (two-sided test).
44
Table 7 Analyses of determinants of post-IPO period annual grants
of total compensation and salary and stock-based components Panel A: Dependent variable – Log of Total Compensation
Earnings
Return on assets
Intercept 11.96 (18.24)a 11.17 (17.64)a
Manufacturing 0.069 (0.31) 0.375 (1.51)Technology 0.096 (0.51) 0.392 (1.85)c
Earnings/ROA: Internet -0.000 (-0.25) -0.739 (-1.82)c
Manufacturing 0.016 (3.54)a -0.300 (-0.54) Technology 0.006 (1.54) -0.130 (-0.23)Stock returns: Internet 0.138 (2.62)a 0.132 (2.49)a
Manufacturing 0.021 (0.12) 0.022 (0.13) Technology 0.045 (0.90) 0.034 (0.67) Market value of equity 0.294 (4.47)a 0.383 (6.24)a
CEO Tenure -0.003 (-0.19) -0.003 (-0.17) Founder -0.14(-0.89) -0.151 (-0.95) CEO Age -0.004 (-0.49) -0.001 (-0.14) Firm Age 0.004 (0.70) 0.005 (0.95) New CEO 0.413 (2.00)b 0.400 (1.92)c
Zero Cash Policy -7.40 (-14.19)a -7.07 (-13.65)a
CEO Ownership % -1.32 (-2.70)a -1.30 (-2.62)a
Stdev Ret 0.107 (0.21) -0.107 (-0.21) PPE_TA 0.201 (0.36) 0.360 (0.64) RD_TA -0.757 (-1.40) -1.478 (-2.29)b
Book-to-Market ratio 0.008 (0.03) 0.110 (0.43) Adjusted R2 .326 .316No. of observations 687 687
See appendix for description of variables. t-statistics in parentheses. a,b, and c denote significance at the 1%, 5% and 10% levels, respectively (two-sided test).
45
Table 7 (cont�d) Analyses of determinants of post-IPO period annual grants of total compensation
and salary and stock-based components Panel B: Dependent variables – Log of Total Cash Compensation and Total Stock Compensation Log of Total Cash Compensation Log of Total Stock Compensation Earnings Return on assets Earnings Return on assets Intercept 12.31 (26.45)a 11.99 (26.84)a 4.49 (1.65)c 2.84 (1.07)
Manufacturing 0.098 (0.61) 0.107 (0.61) 1.030 (1.14) 1.835 (1.79)c
Technology 0.030 (0.22) 0.076 (0.51) 0.166 (0.21) 0.979 (1.09) Earnings/ROA: Internet -0.000 (-0.28) 0.082 (0.03) 0.002 (0.55) -1.646 (-0.75) Manufacturing 0.003 (1.09) 0.005 (0.01) 0.026 (1.83)c -0.007 (0.00) Technology 0.008 (2.71)a 0.800 (2.00)b 0.016 (1.19) -4.046 (-2.18)b
Stock returns: Internet -0.053 (-1.42) -0.062 (-1.66) 0.358 (1.65)c 0.362 (1.68)c
Manufacturing 0.051 (0.42) 0.044 (0.36) 0.679 (1.34) 0.580 (1.19) Technology 0.030 (0.84) 0.019 (0.55) 0.193 (1.42) 0.192 (1.42) Market value of equity
0.095 (2.03)b 0.128 (2.96)a 0.315 (1.13) 0.504 (1.91)c
CEO Tenure 0.015 (1.30) 0.014 (1.19) -0.136 (-2.35) -0.136 (-2.47)a
Founder -0.169 (-1.51) -0.171 (-1.52) 0.263 (0.30) 0.229 (0.37) CEO Age -0.005 (-0.81) -0.003 (-0.43) 0.024 (0.68) 0.033 (0.94) Firm Age 0.005 (1.23) 0.005 (1.17) -0.002 (-0.11) 0.001 (0.05) New CEO -0.354 (-2.42)a -0.357 (-2.43)b 2.083 (2.50)a 2.079 (2.47)a
Zero Cash Policy -10.49 (-28.35)a -10.38 (-28.40)a -1.836 (-0.91) -1.199 (-0.59) CEO Ownership % -0.585 (-1.68)c -0.597 (-1.70)c -8.873 (-5.04)a -9.012 (-5.11)a
Stdev Ret -0.344 (-0.96) -0.365 (-1.01) 1.196 (0.55) 0.210 (0.10) PPE_TA 0.833 (2.10)b 0.929 (2.34)a -2.876 (-1.32) -2.905 (-1.33) RD_TA -0.892 (-2.33)a -0.859 (-1.88)c 2.390 (1.18) 0.808 (-0.31) Book-to-market ratio 0.094 (0.52) 0.142 (0.78) 0.199 (0.22) 0.211 (0.23) Adjusted R2 .574 .572 .084 .080No. of observations 687 687 687 687See appendix for description of variables. t-statistics in parentheses. a,b, and c denote significance at the 1%, 5% and 10% levels, respectively (two-sided test).
46
Table 8
Analyses of determinants of post-IPO period annual grants of total compensation and salary and stock-based components by extent of venture capital involvement
Log of Total Compensation Log of Cash Compensation Log of Stock Compensation Non-venture-
influenced Venture-
influenced VC = non VC?*
Non-venture- influenced
Venture- influenced
VC = non VC?*
No venture influence
Venture influence
VC = no VC?*
Intercept 13.08 (15.56)a 10.11 (10.85)a .0272 12.526 (18.98)a 11.64 (23.18)a .3635 7.41 (2.28)b 1.07 (0.22) .0227
Manufacturing 0.030 (0.10) 0.362 (1.14) .4772 0.088 (0.37) 0.062 (0.36) .9373 0.681 (0.60) 1.787 (1.10) .5516 Technology 0.091 (0.36) 0.409 (1.53) .4168 0.034 (0.17) 0.067 (0.47) .9063 0.030 (0.03) 0.591 (0.43) .9749
Earnings: Internet -0.000 (-0.34) 0.000 (0.27) .3438 -0.000 (-0.39) 0.000 (0.41) .3150 0.002 (0.40) 0.002 (0.30) .3466 Manufacturing 0.011 (1.59) -0.003 (-0.46) .0676 0.012 (2.14)b -0.156 (-5.25)a .0001 0.056 (2.84)a -0.015 (-0.71) .0023 Technology 0.010 (2.28)b -0.015 (-1.11) .0598 0.009 (2.59)a 0.001 (0.17) .2481 0.032 (2.64)a -0.142 (-2.41)a .0042
Stock returns: Internet 0.286 (3.95)a -0.044 (-0.67) .0007 -0.027 (-0.47) -0.065 (-1.83)c .3016 0.815 (3.55)a -0.185 (-0.44) .0002 Manufacturing 0.183 (0.92) -0.263 (-0.82) .1429 0.092 (0.59) 0.028 (0.16) .4159 1.233 (2.45)a -0.567 (-0.36) .0071 Technology 0.080 (1.48) -0.175 (-1.16) .0819 0.039 (0.93) -0.014 (-0.18) .3433 0.236 (1.76) 0.255 (0.32) .0395
Adjusted R2 .442 .155 .618 .459 .132 -.005No. of observations 424 263 424 263 424 263
See appendix for description of variables. t-statistics in parentheses. a, b, c denote significance of coefficients at the 1%, 5% and 10% levels, respectively (two-sided test). * p-values for tests of significance of difference in coefficient between the �non-venture-influenced� and �venture-influenced� models (two-sided tests for intercepts, one-sided tests for performance measures). p-values in bold indicate significance at the 10% level or below. Control variables omitted from table for ease of presentation.
47
Table 9 Results of logistic regressions of CEO turnover on firm performance,
CEO characteristics and other firm characteristics
Earnings Return on assets Intercept -0.92 (0.576) -0.14 (0.931) Manufacturing 0.05 (0.925) -0.29 (0.625) Technology -0.61 (0.247) -0.91 (0.111) Earnings/ROA: Internet 0.01 (0.350) 1.77 (0.179) Manufacturing -0.01 (0.186) -0.14 (0.422) Technology -0.00 (0.403) -0.63 (0.305) Stock returns: Internet -0.88 (0.083)b -1.21 (0.079)b Manufacturing -1.32 (0.019)a -1.30 (0.019)a Technology -0.36 (0.213) -0.25 (0.278)
CEO Tenure -0.03 (0.546) -0.03 (0.486) Founder 0.21 (0.607) 0.24 (0.568) CEO Age -0.01 (0.828) -0.01 (0.710) Firm Age 0.03 (0.188) 0.32 (0.152) CEO Ownership % -2.67 (0.125) -2.62 (0.128) Market value 0.12 (.546) 0.047 (0.788) Venture % -1.31 (0.163) -1.32 (0.153) Significance of model (p-value) 0.0541 0.0478 No. of observations 339 339
See appendix for description of variables. p-values in parentheses. a,b, c denote significance at the 1%, 5% and 10% levels, respectively (one-sided test for performance measures, two-sided
test for other variables).
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