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

References Anderson, M., R. Banker and S. Ravindran, 2000, Executive compensation in the information technology industry, Management Science 4, 530-547. APB Opinion No. 18, The Equity Method of Accounting of Investments in Common Stock, paragraph 17. Baker, M. and P.A. Gompers, 1999, An analysis of executive compensation, ownership, and control in closely held firms, Harvard University working paper. Baker, M. and P.A. Gompers, 2000, The determinants of board structure and function at the initial public offering, Harvard University working paper. Banker, R. and S. Datar, 1989, An empirical evaluation of accounting income numbers, Journal of Accounting Research 21, 21-39. Barry, C. C. Muscarella, J. Peavy III and M. Vetsuypens, 1990, The role of venture capital in the creation of public companies: evidence from the going public process, Journal of Financial Economics 27, 447-476. Benston, G., 1985, The self-serving hypothesis: some evidence, Journal of Accounting and Economics 7, 67-84. Berle, A.A. and G.C. Means, 1932, The modern corporation and private property, New York, Commerce Clearing House, Loose leaf service division of the Corporation Trust Company. Bushman, R.M., Q. Chen, Q., E. Engel and A. Smith, 2000, The sensitivity of corporate governance systems to the timeliness of accounting earnings, University of Chicago working paper. Bushman, R.M., E. Engel, J Milliron and A. Smith, 2000, An analysis of the relation between the stewardship and valuation roles of earnings, University of Chicago working paper. Bushman, R.M., R.J. Indjejikian and A. Smith, 1996, CEO compensation: the role of individual performance evaluation, Journal of Accounting and Economics 21, 161-193. Bushman, R.M. and A. Smith, 2001, Financial accounting information and corporate governance, Forthcoming, Journal of Accounting and Economics. Coughlan, A.T. and R.M. Schmidt, 1985, Executive compensation, managerial turnover, and firm performance: an empirical investigation, Journal of Accounting and Economics 7, 43-66. Demers, E. and B. Lev, 2000, A rude awakening: internet shakeout in 2000, University of Rochester working paper.

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.

35

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).